Up to now, transport systems have mainly been designed by considering time-efficiency, mobility and safety criteria. Today hard constraints on resources savings and environment preservation have to be taken into account at the different phases of design, maintenance and operation of these networks. This study, focused on the operation phase, aimed to provide a common framework for rail and roads energy consumption assessment. For that, the influence of infrastructure characteristics on energy consumption of vehicles was assessed, in a optimization perspective. A method for energy consumptions evaluation by exploiting contact forces models was proposed. Two models were developed, for a road and for a railway, and validated with experimental data of a vehicle on a test track and full-scale measurement of a high speed train on a given line. At last, numerical simulations are worked out with the validated models to exhibit the influence of successions of uphill and downhill on energy consumptions. These simple mechanical models pointed out the differences of the two transportation systems, in terms of developed contact forces and consumed energy.

Road transport largely dominates the transportation demand and energy consumption. Passenger light-duty vehicles (passenger cars and light trucks) are responsible for almost half of the energy consumption of road transport. This energy is mainly supplied by fuels produced using oil resources, increasingly difficult and expensive to exploit. The use of these fuels also generates greenhouse gases, mainly carbon dioxide. This paper analyzes and compares strategies from different domains – the vehicle, the driver and the environment – for reducing carbon dioxide emissions from the use phase of passenger cars. This analysis is based on a general litterature review primarily focused on strategies applicable to OECD countries. A framework for classifying these strategies and the interactions between measures coming from different domains is proposed. The results highlight the possibilities of integration between domains that remain unexplored and that could bring significant gains in terms of emissions reductions.

The health and equity issues related to urban pollution, coupled with the need to assess the consequences of implementing transport policies or new mobility solutions, make it imperative to provide decision-makers with a relevant modeling framework. The coupling of activity-based travel models with environmental models presents a promising approach to thoroughly investigate the interconnected issues related to the impact of road traffic on individual exposure to noise and air pollution. Integrated modeling chains provide a robust framework to comprehensively assess traffic scenarios on a city scale and address issues related to environmental inequalities. This article reviews the recent work in this field to identify both the main contributions and key challenges still to be addressed. It illustrates how the use of a dynamic approach, which considers the intraday dynamics of individual mobilities and pollution concentrations, can contribute to more accurate estimates of the exposure of individuals to pollutants. This modeling approach also has the potential to investigate how the level of exposure depends on the characteristics of the individuals (socioeconomic factors, commuting patterns, location of residence, and main activities). Nonetheless, there are still important challenges to overcome to further enhance the accuracy and applicability of these models: taking into account all types of traffic and transport modes; refining the modeling of exposure to pollution during travel; taking better consideration of microenvironments; and so forth.

Ifsttar and RFF have developed an energy model of high-speed trains in order to determine the influence of infrastructure geometry and environment on train power consumptions. Validation of this model is based on full scale tests performed for the Rhine-Rhone high-speed line acceptance of work (in 2011). This paper aims to evaluate if wind influence is a relevant parameter for the model. This involves numerical determination of aerodynamic coefficients for various wind and ground configurations and their use for the calculation of the aerodynamic efforts. Atmospheric characteristics are extrapolated from meteorological measurements thanks to the AROME numerical model, over the whole Rhine-Rhone line. Most remarkable results show for a moderate train speed (about 47 m/s), a rearward oriented wind of only 5,5 m/s lowers by 30% the power due to aerodynamic forces applied on the train, or raises it similarly if it is forwardly oriented. In conclusion, this work points out that wind influence is of first importance for computing energy consumption.

In the context of reducing the global energy consumptions in transport systems, railways offer many advantages. Therefore the construction of new high speed railways has been planned. This article assesses the impact of the gradient of the railway on the train energy efficiency. This key parameter has a direct influence on the construction and operation phases energy amounts, since low gradients could require considerable civil engineering works. The energy model of the railway operation phase presented in this paper takes into account the infrastructure geometry, the train characteristics and the speed profiles. It is applied to different generic cases in order to illustrate the impact of the infrastructure gradients. The corresponding trajectories are compared from an energy efficiency point of view. Results show that the gradient is not the only one element to take into account. The associated length of ramp or slope is crucial too. For example, it is shown that short section with an important gradient can require less operation energy than lower gradient on longer distances. It is therefore possible to determine a couple of slope/ramp length and gradient for a given rolling stock which contributes to the minimization of the global construction cost and of the operating energy consumption.

Macroalgae are a potentially novel source of nutrition and biologically active molecules. Proliferative species such as Eucheuma denticulatum, Solieria chordalis (red algae) and Sargassum muticum (brown alga) constitute a huge biomass that can be exploited. In this study, we focus on the extraction of polysaccharides from these three macroalgae species and the characterization of cell wall polysaccharides such as carrageenans, fucoidans and alginates by Fourier Transform Infrared spectroscopy with Attenuated Reflectance Module (FTIR-ATR). The comparison of purified extracts with commercial solutions of fucoidans, alginates or carrageenans shows a strong similarity between the spectra. It demonstrates that the methods of extraction that have been used are also suitable purifying technics. Moreover, it validates infrared spectroscopy as a quick, simple and non-destructive method for the accurate analysis of polysaccharides. The FTIR technique applied to samples collected at different periods of the year allowed us to highlight differences in the composition of fucoidans, alginates and carrageenans. Different classes corresponding to the season can be distinguished by statistical multidimensionnal analysis (Principal Component Analysis) showing that the structure of algal polysaccharides, related to bioactivity, depends on the period of harvest. FTIR results showed that S. chordalis and E. denticulatum possess a dominant type of carrageenan called iota-carrageenan. This type of carrageenan is in the majority when the alga is at maturity in its development cycle. During its growth phase, iota-carrageenan precursors can be detected by FTIR spectra, enabling a better control of the extraction and an application of these compounds in various economic sectors. When the alga E. denticulatum is in its juvenile stage, we found traces of kappa-carrageenan and nu-carrageenan polysaccharides in some extracts.

The production by enzymatic treatment of fish protein hydrolysates (FPH) is a promising route to add value to fisheries proteinic co-products (fish frames, heads etc.). Indeed, FPH possess good nutritional properties and biological activities for food and feed uses. Pressure-driven membrane separations such as ultrafiltration (UF) and nanofiltration (NF) can be used after the hydrolysis to increase the specific activities of the FPH. This paper discusses the impact of a two-step UF/NF process producing four different fractions on two industrial FPH with different hydrolysis degrees. Fractionation is carried out in “realistic” conditions for an industrial process, on highly concentrated FPH solutions (about 100 g of dry matter/L) at a high volume reduction factor. For each step, UF or NF, the variation of the permeation flux in the course of the fractionation is discussed according to the FPH hydrolysis degree and the membranes cut-offs. The values of performance indicators defined in terms of nitrogen content are also examined, including the concentration factor (CF), the relative recovery in the retentate (ηR) and the mean and final retention factors (RFm and RFf). Computed values of these indicators are validated through the setting of volume and mass balances around each step. The impact of fractionation on the FPH peptidic population is shown. Peptidic populations are described in terms of chromatographic profiles (SEC–FPLC). The UF fractionation produces a permeate enriched with respect to the FPH smaller than a molecular weight of about 600–750 Dalton, and a retentate enriched in large peptides (above the same MW). A similar behaviour is found for the NF fractionation. Comparing the impact of the UF fractionation on the two hydrolysates allows to conclude that the membrane cut-off is well-suited when comprised between the MWs of the biggest and the most abundant peptides in the FPH.

Proliferation of the introduced brown macro alga Sargassum muticum is known as a natural and hard to control phenomenon occurring along the Atlantic coasts. The phenomenon causes serious troubles for local ecosystems including the alteration of ecosystem structure, the reduction in indigenous biodiversity and economic losses (tourism, aquaculture). However, despite the serious troubles caused by S. muticum, this species contains highly remarkable bioactive metabolites. This macro alga is at present under-exploited and the valorization of its metabolites to give a positive value to this seaweed could be a solution of ecosystemic service. Biorefinery process could be one solution to valorize S. muticum. Comprehensive knowledge concerning the biochemical composition of S. muticum and the impact of environmental factors, particularly seasons, on its composition is a prerequisite before its valorization. In this study, the biochemical composition of S. muticum was evaluated by using classic colorimetric methods based on chemical analysis and Fourier Transform Infra-Red spectrometry (FTIR), and was used as a rapid and safe method that could bring advantages in screening studies and a more comprehensive management and use of seaweed products. Our results are globally in accordance, notably for phenolic compounds, showing the relevance of the use of infrared spectrometry. Moreover, based on the absorption bands of some specific and valuable compounds shown by FTIR, there was a seasonal variation in the polysaccharides, i.e., uronic acids and sulphated compounds, together with phenolic contents of S. muticum.

Energy moderation of the road transportation sector is required to limit climate change and to preserve resources. This work is focused on the moderation of vehicle consumption by optimizing the speed policy along an itinerary while taking into account vehicle dynamics, driver visibility and the road's longitudinal profile. First, a criterion is proposed in order to detect speed policies that are impeding drivers' eco-driving ability. Then, an energy evaluation is carried out and an optimization is proposed. A numerical application is performed on a speed limiting point with 20 usage cases and 5 longitudinal slope values. In the hypothesis of a longitudinal slope of zero, energy savings of 27.7 liter per day could be realized by a speed sign displacement of only 153.6 m. Potential energy savings can increase to up to 308.4 L per day for a −4% slope case, or up to 70.5 L per day for an ordinary −2% slope, with a sign displacement of only 391.5 m. This results in a total of 771,975 L of fuel savings over a 30 year infrastructure life cycle period. Therefore a methodology has been developed to help road managers optimize their speed policies with the aim of moderating vehicle consumption.

The French metropolis, Rouen Normandie, has a project of a new bridge requiring temporary pier in the river Seine during the building phase. The location of this pier in the river is constrained by mechanical reasons related to the construction of the bridge. The purpose of this study is to find a position of this pier in the mechanically constrained area which minimizes vessel traffic obstruction and therefore collision risk. This type of study is classically carried out by using complex and multiple vessel dynamics simulation software in order to assess the risk for a given vessel to crash into the pier. The novelty of this study is to propose a statistical study based on the database of Automatic Identification System (AIS) of the Vessel Traffic Service (VTS) that is an automatic tracking system relying on ships transceivers. The technical objective is to identify low risk areas according to vessel speeds and sizes. Both factors should have an impact on the maneuverability of ships to avoid pier collision risk. Among all trajectories, straight line trajectories are selected based on statistical methods. The computation of prediction intervals of these trajectories delimits navigation zone. If all the straight trajectories are taken into account, the navigation zone extends to the whole river surface, which is not an helping result. However, by focusing on large and high speed vessels trajectories the navigation zone of these weak maneuverable ships is more centered in the middle of the river and represents only 25% of the river area. The complement of this area delineates possible locations of the temporary pier of the bridge in the river that do not disrupt vessel traffic.

Road safety relies mostly on available tire to road grip regarding to the forces required by a vehicle in a given dynamic situation. For example safety issues can occur when deceleration required forces exceeding the tire/road grip potential. Issues are much critical while traveling in a curve with a coupled longitudinal/transverse grip demand. Instrumented vehicles can be used in order to evaluate the available tire to road grip in rolling situations, but it remains linked to a dedicated vehicle and models have to be use to extrapolate these evaluations to various vehicles. The aim of this work is to propose a sensor embedded in the road infrastructure to evaluate the longitudinal and transverse grip demand of any traveling vehicle. A 6 axis sensor is embedded in a road test track, under a piece of the real road upper layer. Measurement are made at a acquisition rate of 2500 Hz and forces measuring ranges are of 2500 daN (vertical axis) and 750 daN (tangential). Measurements are compared to on-board measurement with a vehicle instrumented with dynamometric wheels. Three situations are experienced in a 100 meters curve: traveling at a given speed and traveling while accelerating or braking moderately, and for three vehicle speeds of 40, 60 and 80 km/h. Force evaluation from the two systems are differing of only 5% for the vertical force and 10% for the tangential forces. The differences are lower for the higher grip demands. For example moderate braking from 70 km/h in curve lead to 0.23 and 0.25 longitudinal friction coefficients (LFC) for road sensor and dynamometric wheel, and to 0.17 and 0.19 transversal friction coefficients (TFC). In perspectives, evaluations of an excessive grip demand could result in solutions as lowering the designed speed or improving the road surface layer.

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Energy consumed by road vehicles has a high impact on climate changes; indeed this energy use accounts for 23% of total energy-related Green House Gases (GHG) emissions of 2014 global GHG emissions. GHG emissions are growing constantly year after year, in spite of global objectives (COP) and researches on vehicle efficiency and modal shift. The contribution of the infrastructure to lower this energy is less studied, since it is often seen as immuable or too costly. This paper aims to demonstrate that simple and low-cost solutions exist for that purpose. Particularly a methodology has been developed, based on an optimization of the speed layout over an itinerary in order to improve the eco-driving potential of a given road infrastructure. The key point of this work is that inconsistency often exists between vehicle dynamics, road longitudinal profile and changes in regulation speeds. These changes in speed are defining the speed-sectioning of a route, and an optimization of this speed-sectioning can be easily carried out while displacing or modifying speed signs. The objective of this study is to build an optimized speed sectioning which minimizes the fuel consumption for realistic traffic and various driver behaviours, while maintaining the required safety levels. A progressive optimization loop has been worked out with a Python script including an embedded microscopic road traffic simulator. As a result an optimized speed-sectioning is leading to a gain of 227 ml for 60 minutes of simulated flow of 100 veh/h/lane, for a modification of a single speed changing point. The overall benefits are reduced energy consumption, air pollution and noise which otherwise would have been produced by braking. This work brings an effective optimization tool for road managers and its practical application is passive and inexpensive. This methodology is suitable for rural and urbanized territories and easily adaptable to any type of traffic in various countries. In perspectives, the optimization process could be extended to a full road route and to a wide range of different speed-sectioning layouts.

In a context of climate change, lowering road vehicles consumption is a key point to meet CO2 reduction requirements. In addition to car technological advances, eco-driving is part of the solution but the road infrastructure should ensure its development. In a previous study, a gain of 5% in the spent energy was estimated on specific route by slightly moving some speed signs, but under the assumptions that drivers practice eco-driving and the traffic is free-flow. This paper deepens and widens these first results. The base of this research is to provide a simulation model to study the impact of traffic and speed-sectioning on the environment. Inside this model, the impact of different approach speeds to a speed-sectioning is assessed. The simulation is conducted within the Trafficware Synchro environment where parameters according to road infrastructure, vehicle and driver are based on real traffic data. Moving a speed limitation sign can contribute to a reduction of fuel consumption up to 8% depending on driver structure. This new methodology improves the accuracy of our first results and detects adverse effects as the possible emergence of congestion due to the modification of speed sectioning. In perspective this methodology represents a significant argument in road managers strategy. In addition it also represents an orienting point to investigate different action scenarios and a first step to a global optimization policy in managing road infrastructure.

Efforts to limit climate change should concern the transportation sector which is responsible for roughly a quarter of greenhouse gas emissions. Aside from vehicle's technical progress and driver eco-driving awareness, road infrastructure has a role to play in this environmental aim. At the project stage, the design of roads can avoid energy losses linked to marked ramps, but afterwards, during the use phase, road management can be a lever too. In this use phase framework, our paper is focused on energy saving that can be achieved by managing speed sectioning. The key point is to ensure consistency between vehicle dynamics, road longitudinal profile and speed policy. Indeed, eco-driving could be impeded if a limiting speed sign is encountered on a steep slope or in a sharp turn. In such a situation the speed sign will be qualified as misplaced. Mechanical braking has then to be used instead of simple natural deceleration. In 2018 the French government lowered authorized speed on secondary roads, from 90 to 80 km/h, with road safety as the primary motivation. In order to assess energy impact of speed-sectioning for these two speed limits, experiments have been carried out in four experimental sites. Furthermore criterion and dissipated energy computation have been developed. The developed energy computation yields to determine the expected fuel economy for the entire traffic over a day on a selected route or network. As a result, over consumption for a misplaced speed sign can reach up to 40 liters of fuel per day with an approaching speed of 80 km/h and 50 liters of fuel per day with an approaching speed of 90 km/h according to traffic data. Significant energy savings could therefore be achieved by sign placement optimization.

This paper proposes a methodology to optimize the longitudinal profile of roads according to either an energy consumption or Global Warming Potential (GWP) criterion calculated for both construction and operation phases. For the construction phase assessment, this methodology is based on a earthworks model that computes the geometric differences between the natural terrain and the longitudinal road profile and moreover uses environmental data validated with real experiments. The operation phase is assessed by simulating traffic over a ten-years period. Traffic simulations are based on vehicle dynamic models, also validated with real experiments. The optimization problem is set up in a finite dimensional optimization. A case study illustrates this methodology. By taking into account actual traffic measurements, the optimized profile decreases by 6% the total primary energy consumption and by 8% the GWP.

Le projet VibraSimu, financé par la direction scientifique de l'IFSTTAR, a été conduit de 2017 à 2019 par trois laboratoires de l'établissement : le Lepsis, Ease et le LPC. Le projet vise à mesurer les vibrations d'un vélo, à les modéliser et les reproduire sur simulateur immersif et enfin, à en évaluer l'impact sur le ressenti des participants. Le projet offre ainsi une meilleure connaissance des vibrations transmises au vélo et au cycliste lors de la circulation sur différents revêtements et améliore le simulateur vélo de l'institut en produisant les vibrations liées aux irrégularités de la chaussée. Il montre également la limite des dispositifs grand public (smartphones) pour mesurer ces vibrations.

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In a context of decreasing resources and of climate change, lowering road vehicles consumption is a key point to meet CO2 reduction requirements. In addition to car technological advances, eco-driving is part of the solution but the road infrastructure should ensure its development. This work aims to demonstrate that road energy demand and associated pollutant emissions can be reduced by working out minor optimization of road infrastructure itself. For this to happen, a simple eco-driving potential criterion is built upon infrastructure parameters such as slopes and sight distances. This criterion aims to detect Misplaced Speed-sectioning Positions (MSP) with regard to the Starting Point of Deceleration (SPD); with speed-sectioning being the succession of speed changes along a given route. An enhanced energy waste formulation is then developed to quantify the vehicles energy waste due to misplaced road-signs. Thirdly, a traffic simulation constitutes a framework for energy evaluation; considering a full flow of vehicles, based on real traffic data, and by modeling several driver behaviors. Simulation results show that a significant fuel reduction of up to 5.5% can be achieved locally, simply by moving a road sign, for rural areas and without degrading road safety.

Sargassum muticum is an invasive macroalga that uncontrollable widely grows on the European Atlantic coasts. This macroalga is particularly rich in phenolics (phlorotan-nins) presenting biological activities such as antioxidant, radical-scavenging, antibacte-rial, photoprotective properties, etc. Among the diversity of metabolites produced by the species, phenolic compounds could constitute one of the potential ways of valorization of Sargassum muticum.For the needs of the study, algae were harvested along a latitudinal gradient in Norway, Ireland, France, Spain and Portugal.After extraction, the highest phenolic contents and bioactivities were measured for the samples coming from Norway and Portugal. Consequently, both these countries have been retained in the present work.The extracts are composed of a “pool” of phenolic compounds of molecular weight varying, according to the literature, from 126 Da (phloroglucinol) to 650 kDa. But the most common compounds are comprised between 10 and 100 kDa. With the aim of concentrating and eventually fractionating (i.e. isolating the most active fractions) the phenolic extracts of Sargassum muticum, a few membranes of Molecular Weight Cut-Off 10 kDa were chosen. These membranes were tested by using different technologies: ultrafiltration, centrifugal tube and dialysis.Results show that there is no significant activity in the permeates signifying that the retention rate is about 100 % for the active fractions. Concerning the retentates, results show clearly an increase of the total phenolic contents as well as antioxidant and radical scavenging activities. The best performances are obtained with the centrifugal tubes using 10 kDa membranes.

La Métropole Rouen Normandie souhaitait concevoir une nouvelle passerelle nécessitant des appuis provisoires en Seine. Aussi a-t-elle sollicité l’Ifsttar pour conduire une étude statistique des données de trajectoires, afin de définir les fuseaux de mobilité des navires en fonction notamment de leur vitesse et de leur gabarit, deux facteurs susceptibles d’avoir un impact sur la manoeuvrabilité des navires. Le traitement des données au format SIA a nécessité de recourir à des outils dédiés aux gros fichiers de données. Puis un modèle de régression linéaire a été retenu pour l’analyse des trajectoires rectilignes hors manoeuvres d’accostage. La détermination d’intervalles de prédiction a permis de délimiter les zones de navigation, et donc de mettre en évidence les surfaces du fleuve aptes à accueillir les appuis provisoires.

The objective of this study was to produce, by an enzymatic hydrolysis process at a pilot scale, a saithe (Pollachius virens) hydrolysate with a high antioxidant activity. Design of experiment methodology, based on laboratory-scale experiments, was used to obtain a behavioral reduced model that allows one to determine the optimal operating conditions maximizing the antioxidant activity. Two specifications were studied: the degree of hydrolysis and the antioxidant activity. The effects of the following hydrolysis parameters (temperature, pH, enzyme concentration, and operating time) were studied and presented as response surfaces. From these results, a multifactorial optimization was performed and the Pareto optimal set of efficient solutions was evaluated. The optimal conditions were tested at laboratory scale and then validated by comparison with tests carried out on a pilot plant.

Ultrafiltration membranes can be advantageously used to improve the bioactivity of a saithe protein hydrolysate containing peptides having a size lower than 7 kDa, by fractionating or concentrating some specific molecular weight peptide classes. The aim of this study is to evaluate the behaviour of a 4 kDa membrane in modified polyethersulfone in conditions close to industrial exploitation. This work consists in evaluating the effect of the initial peptide content (30, 90 and 150 mg/mL), the transmembrane pressure (10 and 30 bar), in total recycling modes and the volume reduction factor (until 5) on membrane performances, in terms of permeation flux and selectivity. The peptide content and mass repartition profiles are measured by size exclusion chromatography.It is observed that the pressure and the peptide content, which can act as complementary or antagonist factors, can be adjusted to modify the transmission of peptides and consequently the apparent molecular weight cut-off (MWCO) of the membrane. These results have been directly applied to study the refining of a peptidic fraction lower than 1 kDa having a potential bioactivity (i.e. antioxidant and hypotensive). The change in refining performances with the volume reduction factor (VRF) are discussed, including the recovery yield and the purity of the interesting fraction in permeate and the energy requirements.

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Seaweeds are potentially excellent sources of bio- active metabolites that could represent useful leads in the de- velopment of new functional ingredients in pharmaceutical and cosmetic industries. In the last decade, new marine bioprocess technologies have allowed the isolation of sub- stances with biological properties. The brown alga Sargassum muticum (Yendo) Fensholt (Ochrophyta) was en- zymatically hydrolyzed to prepare water-soluble extracts by using six different commercially available carbohydrate- degrading enzymes and two proteases. Evaluation of 2,2- diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing antiox- idant power (FRAP) antioxidant, tyrosinase, elastase, and bio- film inhibition, antibacterial and antiviral activities as well as evaluation of cytotoxicity were realized for each extract. Total phenolic content was measured for extract characterization, and solid-phase extraction was useful to purify the enzymatic extract. Soluble total phenolic content of S. muticum Viscozyme extract was highest with 6.4% of dry weight. Enzymatic Celluclast and Viscozyme extracts had the lowest value of DPPH IC50 indicating a strong antiradical activity, 0.6 mg mL−1, in comparison with other enzymes. The ferric reducing antioxidant power ranged between 48.7 μM Fe 2+ Eq, digested with Viscozyme, and 60.8 μM Fe 2+ Eq, digested with Amyloglucosidase. Tyrosinase inhibition activity of S. muticum Neutrase extract was 41.3% higher compared to other enzymes. Elastase inhibition activity of S. muticum Shearzyme extract had highest activity (32.8%). All enzymat- ic extracts showed no cytotoxic effect towards the kidney Vero cells. Meanwhile, only S. muticum Neutrase and Alcalase ex- tracts exhibited potential antiviral activity. In addition, S. muticum Viscozyme and Shearzyme extracts showed prom- ising activity in suppressing the biofilm formation against Pseudomonas aeruginosa and Escherichia coli, respectively. Purification of S. muticum Viscozyme extracts by solid-phase extraction managed to concentrate the phenolic content and improve the bioactivity. These results indicate the promising potential of enzyme-assisted followed by solid-phase extrac- tion in recovering phenolic content and in improving its bioactivity.

Eco-driving is an efficient way to preserve energy resources and limit environment impacts. It is first of all a question of driver behaviour and motivation, vehicle characteristics, but infrastructure parameters could favour - or impede- ecodriving. This study aims to qualify this infrastructure influence, for the speed sectioning parameter of roads. A research evaluating the adequacy between speed changes along a route, vehicle dynamics and the road gradient constitute the frame of this work. Indeed this adequacy has been proven to be descriptive of the ecodriving potentiality of a route, as detailed in a previous experimental evaluation in France (Coiret et al [8]). It is reinforced here with the help of experimental evaluation in Bosnia, with a metro-logical reinforcement : differential gps, temporal tagging system at points of interest, roof anemometer for the influence of wind, is now used to have more accurate data. In particular the better altitude measurements increase results quality, with achievable reductions of 5 % of energy consumptions for given route sections with sectioning optimisation (ie : simple speed limit panels repositioning) We have also researched crucial points on how to compare different countries and their legislation, geography, and traffic conditions. Bosnia and Herzegovina and France are in the context, to indicate that an assessment of quality level in eco-driving of the two countries is taken in consideration. Perspectives are given in terms of traffic software generalization of the experimental results and in terms of speed sectioning revisions in order to reduce linked energy losses and CO2 emissions. A route model could then be evaluated, for which speed-sectioning and positioning of amenities (speed bumper, traffic lights) could be optimized in energy use of infrastructure, with a concern not to alter the security features.

The current transport system is not sustainable because of its high consumption of finite resources (mainly oil) and its impact on the environment (air quality, global warming, etc.). In this context, rail has several advantages: lower consumption and emissions than road and air modes, larger passenger flow, etc. That is why, many rail infrastructures are planned in the world. Today, the impact of energy is not taken into account during the project design. At the project phase of new rail infrastructures, it is nowadays important to characterize accurately the energy that will be induced by its operation phase, in addition to other more classical criteria as construction costs and travel time. Current literature consumption models used to estimate railways operation phase are obsolete or not enough accurate for taking into account the newest train or railways technologies. In this paper, an updated model of consumption for high-speed is proposed, based on experimental data obtained from full-scale tests performed on a new high-speed line. The assessment of the model is achieved by identifying train parameters and measured power consumptions for more than one hundred train routes. Perspectives are then discussed to use this updated model for accurately assess the energy impact of future railway infrastructures.

The current transport system is not sustainable because of its high consumption of finite resources (mainly oil) and its impact on the environment (air quality, global warming, etc.). In this context, rail has several advantages: lower consumption and emissions than road and air modes, larger passenger flow, etc. That is why, many rail infrastructures are planned in the world. Today, the impact of energy is not taken into account during the project design. At the project phase of new rail infrastructures, it is nowadays important to characterize accurately the energy that will be induced by its operation phase, in addition to other more classical criteria as construction costs and travel time. Current literature consumption models used to estimate railways operation phase are obsolete or not enough accurate for taking into account the newest train or railways technologies. In this paper, an updated model of consumption for high-speed is proposed, based on experimental data obtained from full-scale tests performed on a new high-speed line. The assessment of the model is achieved by identifying train parameters and measured power consumptions for more than one hundred train routes. Perspectives are then discussed to use this updated model for accurately assess the energy impact of future railway infrastructures.

Les métros automatiques, sans conducteurs, sont en déploiement important depuis des décennies et offrent de hauts niveaux de service et de sécurité. S’affranchir du facteur humain peut en effet augmenter ces niveaux en exploitation courante mais des protocoles robustes de commande sont alors requis pour pallier l’absence des qualités humaines d’anticipation et d’adaptation en situations exceptionnelles. De tels protocoles, dits d’anti‐collision, sont généralement basés sur une performance minimale de freinage garantie associée à un découpage de l’infrastructure en cantons, fixes ou mobiles, assurant qu’il ne puisse y avoir simultanément plus d’un véhicule sur le même canton. En particulier, un système de métro automatique sur pneu est présenté dans cet article. Des résultats d’essais de freinage de rames montrent l’efficacité de traitements visant à améliorer l’adhérence pneumatique/piste de roulement. L’entretien des pistes pour maintenir un bon niveau de freinage est discuté pour les techniques courantes de striage et de grenaillage des pistes. Enfin, une méthodologie pour permettre le suivi des pistes en temps et en espace est proposée. Elle inclut la sélection et l’emploi de matériels d’évaluation de l’adhérence issus du domaine routier.

Rouen métropole a sollicité les capacités de l'Ifsttar dans le domaine du traitement du signal appliqué à l'usage des infrastructures à travers un courriel envoyé le 1er mars 2017 par M Toynan, responsable du service Ouvrage d'art de la métropole de Rouen, à MM Coiret et Vandanjon, chercheurs à l'Ifsttar. Cette sollicitation concerne un ouvrage en projet pour le franchissement de la Seine. L'ouvrage sera de type léger, sous la forme d'une passerelle dédiée aux modes doux (cycles, piétons). Il complètera l'offre de franchissement existante et reliera efficacement des pôles générateurs de déplacements dans l'agglomération, et notamment l'Ecoquartier Luciline en cours de réalisation en rive droite et l'Ecoquartier Flaubert en projet en rive gauche dans le cadre du projet global Seine Cité. L'ouvrage est donc envisagé dans le secteur Ouest de l'agglomération rouennaise, entre les ponts Guillaume Le Conquérant et Gustave Flaubert, soit en traverse de la partie de Seine accueillant régulièrement la grande Armada. Les appuis principaux de la structure seraient situés dans l'alignement des hangars existants. La structure provisoire dite > sera déconstruite préalablement aux travaux de passerelle. A ce jour, il n'est pas envisagé d'implanter d'appui définitif en Seine. Néanmoins, le recours à des appuis intermédiaires en phase réalisation semble incontournable. De même, la définition d'un gabarit de passe navigable influe sur la définition de la limite basse d'intrados d'ouvrage et donc sur la définition des accès. Seule une connaissance plus précise des trajectoires fluviales entre le Pont Guillaume le Conquérant en amont et le Pont Flaubert en aval permettra donc de gagner en précision sur la définition des implantations possibles d'appuis provisoires puis sur la définition du gabarit fluvial définitif. À cet effet, l'Ifsttar a été sollicité pour une étude statistique de trajectoire de navires, selon un cahier des charges qui est donné en annexe au présent document. L'Ifsttar a répondu à ce cahier des charges en rédigeant une proposition technique, également en annexe à ce document, dont le produit est un rapport d'étude sur les trajectoires fluviales sur la section considérée. Une réunion de lancement a eu lieu le 11 mai 2017 dans les locaux de Rouen métropole. Ce document est la troisième version de ce rapport d'étude. Une première version a été envoyée le 17 juin afin d'échanger avec la Métropole Rouen Normandie. Ce document a été le support d'une réunion téléphonique avec la métropole de Rouen le 27 juin afin, notamment, de préparer une réunion entre la métropole et le grand port maritime de Rouen. Nous avons abouti à une deuxième version envoyée le 3 juillet 2017 afin de fournir des données opérationnelles pour la métropole. Suite à des relectures internes, nous avons modifié cette deuxième version en améliorant sa forme afin d'aboutir à cette version qui est remise lors de la réunion de présentation des résultats du 11 juillet 2017. Ce rapport est découpé en 10 chapitres. Tout d'abord, la structure des données, que nous avons obtenues par le port maritime, est expliquée. Les grandes étapes du traitement de ces données sont présentées dans le chapitre suivant. Puis, les résultats de ce traitement sont affichées sous forme de graphiques pour chaque trimestre de l'année 2016 dans les chapitres 4 à 8. Enfin, les deux dernier chapitres discutent les résultats et conclut le rapport.

Nova'TP, commission TP de NOVABUILD, a initié un groupe de travail visant à favoriser l'innovation dans les marchés publics de travaux, grâce à l'élaboration de cahier des charges décrivant les performances attendues plutôt que les moyens de les atteindre. Cette démarche s'est appuyée sur l'exemple concret du choix des matériaux des pistes cyclables, qui sont intégrées à la plupart des aménagements réalisés sur l'espace public. La première étape du projet a consisté à définir les critères objectifs de performance de ces matériaux, afin de répondre aux enjeux de confort, de développement durable, de coût... exprimés par les maitres d'ouvrage. Sur certains critères, comme le confort, l'absence de référentiel existant pour les infrastructures cyclables, nous a conduit à développer une démarche innovante, en adaptant l'usage du Vel'Audit (Îlo instrumenté, prévu initialement pour l'inspection à haut rendement d'aménagements cyclables). Les matériaux déjà couramment utilisés pour ce type d'infrastructure ont été caractérisés selon ces critères. Ces données ont ensuite été regroupées dans une application, développée pour faciliter l'analyse et la comparaison des offres par les maîtres d'ouvrage. Cette application permet de comparer des matériaux conventionnels entre eux ou avec des matériaux innovants sous un aspect performentiel. Ce logiciel d'aide à la décision a été testé par Nantes Métropole sur plusieurs opérations d'aménagement, pour Îrifier sa pertinence et proposer certaines évolutions.

Les collectivités françaises développent de plus en plus d'aménagement cyclables, et il apparaît donc plus d'attentes concernant la sécurité de ces aménagements, leur confort, leur durabilité, leur gestion et entretien... Si pour le réseau routier général, les maîtres d'ouvrages disposent d'outils d'aide à la décision, basés sur des critères tels que la sécurité, la mobilité, l'environnement et le coût, les voies cyclables ne sont que partiellement concernées par ces outils. Ce travail vise à répondre aux attentes des gestionnaires de réseaux cyclables et a été réalisé dans le cadre du groupe de travail « Nova-TP » sur l'innovation dans les transports. En première partie de ce travail, L'outil Vel'audit est présenté. DériÎ des outils routiers, Vel'Audit est un Îlo instrumenté qui permet de réaliser des releÎs d'images ensuite exploitables à l'aide du logiciel IREVE. Ce diagnostic permet à la fois de caractériser l'infrastructure et d'identifier des défauts de cyclabilité. Vél'audit dispose aussi d'une centrale inertielle mesurant les vibrations subies par le Îlo et conduisant au calcul d'un indicateur confort indexé à la vitesse d'avancement. Pour l'aspect sécurité, le SRT (Skid Resistance Tester) est ensuite présenté, comme un des moyens de mesure de l'adhérence exploité pour les routes et pouvant être directement transposé aux pistes cyclables. Des essais de validité sur piste cyclable sont ensuite discutés et, en perspectives, le développement d'un matériel utilisable continûment sur itinéraire, inspiré du Grip-Tester, est envisagé en prolongement des mesures ponctuelles du SRT. Ainsi différentes techniques d'auscultations routières éprouÎes peuvent répondre aux besoins émergents des gestionnaires d'infrastructures cyclables, tout en s'adaptant aux caractéristiques de ces déplacements cyclables. Ces transpositions sont encore peu investie alors même que les besoins existent et qu'en finalité cela pourrait aboutir à la construction d'un indice de qualité cyclable (IQCy) à l'image de l'IQRN routier.

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The energy associated with the use of road infrastructure exceeds in few years the energy needed for its construction. The link between infrastructure and use energy has not been, however, studied in depth, particularly as the legitimate transport societal expectations are related to efficiency and safety. However, we can consider reducing the energy use by working out minor optimizations of the road infrastructure itself, which is a major challenge in a context of overall decrease of resources and increasing pressures on the environment. Experimental work is carried out here to develop one of these optimizations by improving the eco-driving potential of roads. It is based on the adequacy between vehicles dynamics, the road longitudinal profile and the speed sectioning of the infrastructure. This sectioning corresponds to the succession of speed limitations (road signs, roundabouts, intersections ...). It may allow drivers to eco-drive or not, depending on dynamics, slopes, and secondary parameters as driver reaction time or distance of visibility. Optimal speed sectioning aims to limit the mechanical braking needed by potential energy reduction, due to slopes, which can be encountered simultaneously with the needed kinetic energy reduction. Evaluation has been made on actual road sections, while recording both vehicle dynamics, driver commands, road signs positions and road longitudinal profile. Results show that energy consumption of vehicles approaching a speed reduction sign can be reduced by moving backward this sign of about 700 meters, without penalizing the primary safety function. The associated gain, for this optimization, has been evaluated to 14 liters of fuel per day for one of the experimental sites, considering traffic data. Application of this method on a network could then lead to considerable energy saving by allowing eco-driving.

The photoadaptive responses of macroalgal communities to abiotic stresses have been studied, and a number of UV-absorbing molecules have been identified. Among these compounds, photoprotective compounds such as mycosporine-like amino acids and carotenoids have been isolated from various red macroalgal species. However, several substances still need to be characterized. We describe the preparation of photoprotective extracts obtained from Solieria chordalis. Two solvents, 2-octyl dodecanol and octyldodecyl ester of L-pyrrolidone carboxylic acid, were selected based on their cosmetic functions for performing an ultrasound-assisted extraction. The efficiency of extraction was monitored by spectrophotometry and in vitro photoprotective activity measurements. 2-Octyl dodecanol and octyldodecyl ester of L-pyrrolidone carboxylic acid extracts showed maximum absorption wavelengths ranging from 280 to 340 nm and 270 to 350 nm, respectively. The anti UV-B capacity for protecting a synthetic chlorophyll solution was assessed by measuring its pseudo first-order degradation kinetics at room temperature. Under irradiation at 312 nm, chlorophyll introduced in the 2-octyl dodecanol S. chordalis extract showed the slowest degradation kinetics with a half-life t(1/2) of 121.0 min. Several compounds were detected in the seaweed

Current transport systems are not likely to be sustainable, since energy resources may be less accessible, facing a rapidly growing demand and because of environmental constrains. In this context a great interest arose for sharing environmental assessment practices between infrastructures owners and researchers. For this present work a partnership between RFF and Ifsttar was decided to study environmental effects and energy consumption for railways life cycle. It paves the way to a full life cycle analysis (LCA) for environmental burdens of railway infrastructures and aims at identifying the best design practices at the project level related to environmental criteria. This LCA takes into account earthwork, railway structure and the operation phase, i.e., the analysis performed is based on the estimation of energy consumptions due to construction, maintenance and on the traffic. Results of this work could enhance practices for environment preservation for the plan of building 4000 kilometres of new high-speed railways, decided in the French National Transport infrastructure scheme. Applying LCA to the project phase is a rather new approach. It requires defining a global functional unit as a basic hypothesis of any study, different from the previous studies. Then, the lifecycle subsystems are successively investigated (construction, maintenance and use) to determine the best way for project Functional Unit definition and further assessment method application.

Viability theory proposes geometric metaphors in addition to classical ordinary differential equation analysis. In this paper, advantages of applying viability theory to road safety domain are presented. The exact issue is to determine if, from an initial state of a vehicle/road/driver system, a soft controls strategy is compatible with a safe driving sequence. The case of a car negotiating a curve is considered. The application of the viability theory to this issue offers the advantage to avoid classical full computing of the system. Instead of that, it consists on verifying that the states and the controls belong to a subset called the viability kernel. The construction and the use of the viability kernel for a vehicle system dynamic is proposed by using support vector machines algorithm. Then, the applicability of this theory is demonstrated through experimental tests. This innovative application of the viability theory to vehicle dynamics with road safety concerns could benefit to robust embedded warning systems.

Sargassum muticum, an invasive brown macroalga presently distributed along European Atlantic coasts from southern Portugal to the south coast of Norway, was studied on a large geographical scale for its production of phenolic compounds with potential industrial applications and their chemical and biological activities. S. muticum can produce high biomass in Europe, which could be exploited to supply such compounds. S. muticum was collected in Portugal, Spain, France, Ireland and Norway (three sites/country) to examine the effect of the latitudinal cline and related environmental factors. Assays focused particularly on polyphenols and their activities. Crude acetone-water extracts were purified using solid phase extraction (SPE) and antioxidant and antimicrobial activities of crude extracts and semi-purified fractions measured. Total phenolic content was assessed by colorimetric Folin-Ciocalteu assay and reactive oxygen species activities by 2,2-diphenyl-1-picrylhydrazyl, reducing power, β-carotene bleaching method and xanthine oxidase assay. Antibacterial activities were tested on terrestrial and marine strains to evaluate potential use in biomedical and aquaculture fields. Purified active phlorotannins, isolated by SPE, were identified using NMR. Phenolic contents differ clearly among countries and among sites within countries. Quality did not change between countries, however, although there were some slight differences in phlorethol type. Additionally, some fractions, especially from the extreme north and south, were very active. We discuss this in relation to environmental conditions and the interest of these compounds. S. muticum represents a potential natural source of bioactive compounds and its collection could offer an interesting opportunity for the future management of this species in Europe.

In the hardening energy context, the transport sector which constitutes a large worldwide energy demand has to be improving for decrease energy demand and global warming impacts. In a controversial situation where subsists an increasing demand for long-distance and high-speed travels, high-speed trains offer many advantages, as consuming significantly less energy than road or air transports. At the project phase of new rail infrastructures, it is nowadays important to characterize accurately the energy that will be induced by its operation phase, in addition to other more classical criteria as construction costs and travel time. Current literature consumption models used to estimate railways operation phase are obsolete or not enough accurate for taking into account the newest train or railways technologies. In this paper, an updated model of consumption for high-speed is proposed, based on experimental data obtained from full-scale tests performed on a new high-speed line. The assessment of the model is achieved by identifying train parameters and measured power consumptions for more than one hundred train routes. Perspectives are then discussed to use this updated model for accurately assess the energy impact of future railway infrastructures.

A comparative study between "alternative" extraction processes such as centrifugal partition extraction (CPE), supercritical fluid extraction (SFE) and pressurized liquid extraction (PLE) and classical solid/liquid used in the laboratory are currently focusing on the efficiency (selectivity and productivity) to obtain bioactive phenolic compounds from the phaeophyte Sargassum muticum model. The choice of the best process was based on several measurements: (i) the total phenolic content measured by the colorimetric Folin-Ciocalteu assay, (ii) radical scavenger and antioxidant activities assessed by the DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging assay, and the β-carotene bleaching method and finally (iii) the method productivity. Irrespective of the solvent used in the processes, alternative methods are always sharply more effective than classical ones. With the exception of SFE which does not allow extracting the totality of the active phenolic compounds, two of the other extraction methods were particularly promising. First, CPE afforded the most important yields in concentrated phenolic compounds (PC) (22.90±0.65% DW) also displaying the best activities (0.52±0.02 and 0.58±0.19 mg/mL for IC50 and AAC700, respectively). Secondly, PLE using an EtOH:water mixture 75:25 (v/v) allowed a good PC extraction (10.18±0.25% DW) with huge efficiency. Despite a lesser activity of the extracts (0.77±0.01 and 1.59±0.15 mg/mL for IC50 and AAC700, respectively) PLE is a green process and potentially complies European norms requirements for the prospective valorization of phenolic compounds from S. muticum in Brittany.

Viability theory proposes geometric metaphors in addition to classical ordinary differential equation analysis. This theory is applied on a vehicle cornering. The issue is to determine if a state of the system is compatible with a soft controls strategy which leads the car to the end of the corner. The viability theory offers tools which enable to answer to this question without computing in real time these controls. The issue resumes to verify that this state belongs to a set called the viability kernel. The construction and the use of the viability kernel for a vehicle system dynamic is proposed by using Support Vector Machines algorithm. The applicability of this theory is demonstrated through experimental tests. It is the first time that the viability theory is applied to vehicle dynamics with road safety concerns.

Five organic tubular nanofiltration membranes of various material and molecular weight cut-off (MWCO) were tested for the enrichment of a fish (saithe, Pollachius virens) hydrolysate in low molecular weight antioxidant peptides (< 2 kDa). The effect of membrane material and MWCO on permeation flux, hydrolysate adsorption extent, membrane cleaning and peptides retention was investigated in low fouling conditions in order to limit concentration polarization effects. Water permeation fluxes appeared sensitive both to the MWCO and the membrane material. Membranes in polyethersulfone (PES), a highly hydrophobic material, exhibited lower fluxes than modified polyethersulfone (m-PES) and polysulfone (PS) membranes. The 4 kDa m-PES membrane was found to be the most adapted to the objective in terms of flux and retention factor. The 4 kDa m-PES and 8 kDa PS membranes could also be used in series to recover medium-size peptides. (c) 2008 Elsevier Ltd. All rights reserved.

BACKGROUND: Numerous studies have demonstrated that in vitro controlled enzymatic hydrolysis of fish and shellfish proteins leads to bioactive peptides. Ultrafiltration (UF) and/or nanofiltration (NF) can be used to refine hydrolysates and also to fractionate them in order to obtain a peptide population enriched in selected sizes. This study was designed to highlight the impact of controlled UF and NF on the stability of biological activities of an industrial fish protein hydrolysate (FPH) and to understand whether fractionation could improve its content in bioactive peptides. RESULTS: The starting fish protein hydrolysate exhibited a balanced amino acid composition, a reproducible molecular weight (MW) profile, and a low sodium chloride content, allowing the study of its biological activity. Successive fractionation on UF and NF membranes allowed concentration of peptides of selected sizes, without, however, carrying out sharp separations, some MW classes being found in several fractions. Peptides containing Pro, Hyp, Asp and Glu were concentrated in the UF and NF retentates compared to the unfractionated hydrolysate and UF permeate, respectively. Gastrin/cholecystokinin-like peptides were present in the starting FPH, UF and NF fractions, but fractionation did not increase their concentration. In contrast, quantification of calcitonin gene-related peptide (CGRP)-like peptides demonstrated an increase in CGRP-like activities in the UF permeate, relative to the starting FPH. The starting hydrolysate also showed a potent antioxidant and radical scavenging activity, and a moderate angiotensin-converting enzyme (ACE)-1 inhibitory activity, which were not increased by UF and NF fractionation. CONCLUSION: Fractionation of an FPH using membrane separation, with a molecular weight cut-off adapted to the peptide composition, may provide an effective means to concentrate CGRP-like peptides and peptides enriched in selected amino acids. The peptide size distribution observed after UF and NF fractionation demonstrates that it is misleading to characterize the fractions obtained by membrane filtration according to the MW cut-off of the membrane only, as is currently done in the literature. Copyright © 2010 Society of Chemical Industry

Up to now, transport systems have mainly been designed by considering time-efficiency, mobility and safety criteria. Today hard constraints on resources savings and environment preservation have to be taken into account at the different phases of design, maintenance and operation of these networks. This study, focused on the operation phase, aimed to provide a common framework for rail and roads energy consumption assessment. For that, the influence of infrastructure characteristics on energy consumption of vehicles was assessed, in a optimization perspective. A method for energy consumptions evaluation by exploiting contact forces models was proposed. Two models were developed, for a road and for a railway, and validated with experimental data of a vehicle on a test track and full-scale measurement of a high speed train on a given line. At last, numerical simulations are worked out with the validated models to exhibit the influence of successions of uphill and downhill on energy consumptions. These simple mechanical models pointed out the differences of the two transportation systems, in terms of developed contact forces and consumed energy.

Road transport largely dominates the transportation demand and energy consumption. Passenger light-duty vehicles (passenger cars and light trucks) are responsible for almost half of the energy consumption of road transport. This energy is mainly supplied by fuels produced using oil resources, increasingly difficult and expensive to exploit. The use of these fuels also generates greenhouse gases, mainly carbon dioxide. This paper analyzes and compares strategies from different domains – the vehicle, the driver and the environment – for reducing carbon dioxide emissions from the use phase of passenger cars. This analysis is based on a general litterature review primarily focused on strategies applicable to OECD countries. A framework for classifying these strategies and the interactions between measures coming from different domains is proposed. The results highlight the possibilities of integration between domains that remain unexplored and that could bring significant gains in terms of emissions reductions.

The health and equity issues related to urban pollution, coupled with the need to assess the consequences of implementing transport policies or new mobility solutions, make it imperative to provide decision-makers with a relevant modeling framework. The coupling of activity-based travel models with environmental models presents a promising approach to thoroughly investigate the interconnected issues related to the impact of road traffic on individual exposure to noise and air pollution. Integrated modeling chains provide a robust framework to comprehensively assess traffic scenarios on a city scale and address issues related to environmental inequalities. This article reviews the recent work in this field to identify both the main contributions and key challenges still to be addressed. It illustrates how the use of a dynamic approach, which considers the intraday dynamics of individual mobilities and pollution concentrations, can contribute to more accurate estimates of the exposure of individuals to pollutants. This modeling approach also has the potential to investigate how the level of exposure depends on the characteristics of the individuals (socioeconomic factors, commuting patterns, location of residence, and main activities). Nonetheless, there are still important challenges to overcome to further enhance the accuracy and applicability of these models: taking into account all types of traffic and transport modes; refining the modeling of exposure to pollution during travel; taking better consideration of microenvironments; and so forth.

Identifying the drag force coefficient and the rolling resistance coefficient of a vehicle is not an easy task, especially when not using a wind tunnel. This paper proposes an easy method using light experimental means to assess these coefficients in the case of a cargo-bike. Free deceleration measurement is performed. An identification method based on the least squares method is then proposed and discussed.

Energy moderation of the road transportation sector is required to limit climate change and to preserve resources. This work is focused on the moderation of vehicle consumption by optimizing the speed policy along an itinerary while taking into account vehicle dynamics, driver visibility and the road's longitudinal profile. First, a criterion is proposed in order to detect speed policies that are impeding drivers' eco-driving ability. Then, an energy evaluation is carried out and an optimization is proposed. A numerical application is performed on a speed limiting point with 20 usage cases and 5 longitudinal slope values. In the hypothesis of a longitudinal slope of zero, energy savings of 27.7 liter per day could be realized by a speed sign displacement of only 153.6 m. Potential energy savings can increase to up to 308.4 L per day for a −4% slope case, or up to 70.5 L per day for an ordinary −2% slope, with a sign displacement of only 391.5 m. This results in a total of 771,975 L of fuel savings over a 30 year infrastructure life cycle period. Therefore a methodology has been developed to help road managers optimize their speed policies with the aim of moderating vehicle consumption.

Ce papier présente une nouvelle méthode à erreur de sortie en deux étapes pour l'identification en boucle fermée des paramètres inertiels, de frottements et de raideur d'un axe de robot avec flexibilité articulaire localisée. Cette méthode utilise uniquement l'effort et la position du moteur, sans aucune mesure de flexibilité. La première étape identifie la fréquence du mode rigide asservi et la fréquence du mode flexible à entrée bloquée, en utilisant un modèle haute fréquence double intégrateur du robot. L'identification utilise une méthode à erreur de sortie sur la position du moteur. Ces deux paramètres de fréquence optimaux sont ensuite utilisés dans la deuxième étape pour l'identification des paramètres dynamiques du robot par une méthode à erreur de sortie sur l'effort moteur. Cette méthode récente (DIDIM) qui utilise les modèles d'identification directe et inverse du robot permet d'obtenir une convergence des paramètres très rapide et insensible aux conditions initiales. Une validation expérimentale sur un robot un axe montre l'efficacité de la nouvelle méthode comparée à deux méthodes à erreur de sortie classiques.

The French metropolis, Rouen Normandie, has a project of a new bridge requiring temporary pier in the river Seine during the building phase. The location of this pier in the river is constrained by mechanical reasons related to the construction of the bridge. The purpose of this study is to find a position of this pier in the mechanically constrained area which minimizes vessel traffic obstruction and therefore collision risk. This type of study is classically carried out by using complex and multiple vessel dynamics simulation software in order to assess the risk for a given vessel to crash into the pier. The novelty of this study is to propose a statistical study based on the database of Automatic Identification System (AIS) of the Vessel Traffic Service (VTS) that is an automatic tracking system relying on ships transceivers. The technical objective is to identify low risk areas according to vessel speeds and sizes. Both factors should have an impact on the maneuverability of ships to avoid pier collision risk. Among all trajectories, straight line trajectories are selected based on statistical methods. The computation of prediction intervals of these trajectories delimits navigation zone. If all the straight trajectories are taken into account, the navigation zone extends to the whole river surface, which is not an helping result. However, by focusing on large and high speed vessels trajectories the navigation zone of these weak maneuverable ships is more centered in the middle of the river and represents only 25% of the river area. The complement of this area delineates possible locations of the temporary pier of the bridge in the river that do not disrupt vessel traffic.

Road safety relies mostly on available tire to road grip regarding to the forces required by a vehicle in a given dynamic situation. For example safety issues can occur when deceleration required forces exceeding the tire/road grip potential. Issues are much critical while traveling in a curve with a coupled longitudinal/transverse grip demand. Instrumented vehicles can be used in order to evaluate the available tire to road grip in rolling situations, but it remains linked to a dedicated vehicle and models have to be use to extrapolate these evaluations to various vehicles. The aim of this work is to propose a sensor embedded in the road infrastructure to evaluate the longitudinal and transverse grip demand of any traveling vehicle. A 6 axis sensor is embedded in a road test track, under a piece of the real road upper layer. Measurement are made at a acquisition rate of 2500 Hz and forces measuring ranges are of 2500 daN (vertical axis) and 750 daN (tangential). Measurements are compared to on-board measurement with a vehicle instrumented with dynamometric wheels. Three situations are experienced in a 100 meters curve: traveling at a given speed and traveling while accelerating or braking moderately, and for three vehicle speeds of 40, 60 and 80 km/h. Force evaluation from the two systems are differing of only 5% for the vertical force and 10% for the tangential forces. The differences are lower for the higher grip demands. For example moderate braking from 70 km/h in curve lead to 0.23 and 0.25 longitudinal friction coefficients (LFC) for road sensor and dynamometric wheel, and to 0.17 and 0.19 transversal friction coefficients (TFC). In perspectives, evaluations of an excessive grip demand could result in solutions as lowering the designed speed or improving the road surface layer.

Analyzing spatial structures of transportation data at various scales can be of prime interest to transportation planning and governance. In recent years, multi-scale spatial analysis methods have been developed and used in fields like ecology and geography, but only a few studies have applied these methods to transportation data. However, such methods can provide an efficient exploratory tool for: identifying those scales at which transportation data vary spatially; modeling the spatial structures at each scale; and determining the processes at work that explain these spatial structures. This paper describes and demonstrates how a multi-scale spatial analysis method, namely distance-based Moran's eigenvector maps (dbMEM), can be applied to study the spatial layout of car ownership. For this analysis, we rely on aggregated census data for small statistical areas within France's Loire-Atlantique administrative region. At first, 176 spatial vectors representing spatial patterns with a positive autocorrelation are constructed. Among the 176 vectors, only 23 significant ones are retained after performing a regression with car ownership as the dependent variable. Next, we divide these spatial vectors into three sub-models representing three spatial scales: broad scale, medium scale, and fine scale. Lastly, we identify a set of sociodemographic factors capable of explaining the spatial variation at each scale, i.e.: the broad-scale variation is mainly explained by population density, couples with children and income variables; the medium scale by couples with children, share of individuals in the 25-54 year age range and income; and the fine scale by couples with children and income variables.

Ce rapport est le deuxième rapport prévu au sein de ce contrat, écrit par l'équipe universitaire à destination de la SNCF dans le cadre de la convention de co-encadrement SNCF/UniversitéGustaveEiffel (anciennement Ifsttar) accompagne cette thèse (No Ifsttar : RP1-E19045) sous la responsabilité scientifique de Jean Calio, expert Data, Mobilité et Territoires et Développement Durable de la SNCF et de Pierre-Olivier Vandanjon.

This paper presents a framework to tackle the problem, which has received little attention in the literature, of adding variables to a synthetic population from aggregate data. The work herein thus enriches the existing literature by proposing a new and e icient methodology to meet this practical need. The methodology integrates three distinct stages, the first of which theoretically models the problem as a multinomial distribution. The addition of a new variable is formulated as an entropy maximization using the variables available in both the synthetic population and aggregate data. Solving this problem (in our specific case study) is not possible due to the large number of constraints involved. The second stage then presents a heuristic yielding a practical solution to the problem. This heuristic combines Bayes' theorem with the cross-entropy minimization algorithm. However, given the large number of parameters to be estimated by the proposed heuristic, some of the results obtained prove to be invalid. To rectify this shortcoming, a post-processing method is applied during a third stage to ensure the consistency of our results. The methodology is described in great detail, and examples are provided for a better understanding of these three stages. Also, this methodology is applied to a real-world case study. An income is allocated to each of the 157 000 households in the French city of Nantes based on aggregate data from the FiLoSoFi database. Income constitutes an essential microsimulation variable for taking many social and economic aspects into account (e.g. household purchasing power, redistribution policy, tax policy). Special attention is also paid to the reproducibility of our results with the databases and R-scripts used, all of which are freely available. This method remains general and is indeed applicable to other variables with available aggregate data.

Energy consumed by road vehicles has a high impact on climate changes; indeed this energy use accounts for 23% of total energy-related Green House Gases (GHG) emissions of 2014 global GHG emissions. GHG emissions are growing constantly year after year, in spite of global objectives (COP) and researches on vehicle efficiency and modal shift. The contribution of the infrastructure to lower this energy is less studied, since it is often seen as immuable or too costly. This paper aims to demonstrate that simple and low-cost solutions exist for that purpose. Particularly a methodology has been developed, based on an optimization of the speed layout over an itinerary in order to improve the eco-driving potential of a given road infrastructure. The key point of this work is that inconsistency often exists between vehicle dynamics, road longitudinal profile and changes in regulation speeds. These changes in speed are defining the speed-sectioning of a route, and an optimization of this speed-sectioning can be easily carried out while displacing or modifying speed signs. The objective of this study is to build an optimized speed sectioning which minimizes the fuel consumption for realistic traffic and various driver behaviours, while maintaining the required safety levels. A progressive optimization loop has been worked out with a Python script including an embedded microscopic road traffic simulator. As a result an optimized speed-sectioning is leading to a gain of 227 ml for 60 minutes of simulated flow of 100 veh/h/lane, for a modification of a single speed changing point. The overall benefits are reduced energy consumption, air pollution and noise which otherwise would have been produced by braking. This work brings an effective optimization tool for road managers and its practical application is passive and inexpensive. This methodology is suitable for rural and urbanized territories and easily adaptable to any type of traffic in various countries. In perspectives, the optimization process could be extended to a full road route and to a wide range of different speed-sectioning layouts.

In a context of climate change, lowering road vehicles consumption is a key point to meet CO2 reduction requirements. In addition to car technological advances, eco-driving is part of the solution but the road infrastructure should ensure its development. In a previous study, a gain of 5% in the spent energy was estimated on specific route by slightly moving some speed signs, but under the assumptions that drivers practice eco-driving and the traffic is free-flow. This paper deepens and widens these first results. The base of this research is to provide a simulation model to study the impact of traffic and speed-sectioning on the environment. Inside this model, the impact of different approach speeds to a speed-sectioning is assessed. The simulation is conducted within the Trafficware Synchro environment where parameters according to road infrastructure, vehicle and driver are based on real traffic data. Moving a speed limitation sign can contribute to a reduction of fuel consumption up to 8% depending on driver structure. This new methodology improves the accuracy of our first results and detects adverse effects as the possible emergence of congestion due to the modification of speed sectioning. In perspective this methodology represents a significant argument in road managers strategy. In addition it also represents an orienting point to investigate different action scenarios and a first step to a global optimization policy in managing road infrastructure.

Efforts to limit climate change should concern the transportation sector which is responsible for roughly a quarter of greenhouse gas emissions. Aside from vehicle's technical progress and driver eco-driving awareness, road infrastructure has a role to play in this environmental aim. At the project stage, the design of roads can avoid energy losses linked to marked ramps, but afterwards, during the use phase, road management can be a lever too. In this use phase framework, our paper is focused on energy saving that can be achieved by managing speed sectioning. The key point is to ensure consistency between vehicle dynamics, road longitudinal profile and speed policy. Indeed, eco-driving could be impeded if a limiting speed sign is encountered on a steep slope or in a sharp turn. In such a situation the speed sign will be qualified as misplaced. Mechanical braking has then to be used instead of simple natural deceleration. In 2018 the French government lowered authorized speed on secondary roads, from 90 to 80 km/h, with road safety as the primary motivation. In order to assess energy impact of speed-sectioning for these two speed limits, experiments have been carried out in four experimental sites. Furthermore criterion and dissipated energy computation have been developed. The developed energy computation yields to determine the expected fuel economy for the entire traffic over a day on a selected route or network. As a result, over consumption for a misplaced speed sign can reach up to 40 liters of fuel per day with an approaching speed of 80 km/h and 50 liters of fuel per day with an approaching speed of 90 km/h according to traffic data. Significant energy savings could therefore be achieved by sign placement optimization.

This article describes the generation of a detailed two-layered synthetic population of households and individuals for French municipalities. Using French census data, four synthetic reconstruction methods associated with two probabilistic integerization methods are applied. The paper offers an in-depth description of each method through a common framework. A comparison of these methods is then carried out on the basis of various criteria. Results show that the tested algorithms produce realistic synthetic populations with the most efficient synthetic reconstruction methods assessed being the Hierarchical Iterative Proportional Fitting and the relative entropy minimization algorithms. Combined with the Truncation Replication Sampling allocation method for performing integerization, these algorithms generate household-level and individual-level data whose values lie closest to those of the actual population.

This paper proposes a methodology to optimize the longitudinal profile of roads according to either an energy consumption or Global Warming Potential (GWP) criterion calculated for both construction and operation phases. For the construction phase assessment, this methodology is based on a earthworks model that computes the geometric differences between the natural terrain and the longitudinal road profile and moreover uses environmental data validated with real experiments. The operation phase is assessed by simulating traffic over a ten-years period. Traffic simulations are based on vehicle dynamic models, also validated with real experiments. The optimization problem is set up in a finite dimensional optimization. A case study illustrates this methodology. By taking into account actual traffic measurements, the optimized profile decreases by 6% the total primary energy consumption and by 8% the GWP.

Synthetic population is used in many transport models ranging from trip-based, hybrid trip, tour-based, and activity-based models. As mobility decisions depend on both individuals' characteristics and family situation, generating a two-layered population that takes into account not only the individual level but also household level is essential. In the literature, three main categories of methods for two-layered population generation have been proposed. These categories are synthetic reconstruction (SR), combinatorial optimization (CO), and statistical learning (SL). SR and CO methods produce synthetic populations by means of replicating individuals, whereas SL methods generate a population following a joint probability estimation. However, selecting a generation process is not straightforward as it depends on input data and synthetic population characteristics. To the best of our knowledge, no clear methodology for selecting between these methods exists. The main objectives of this paper are to provide (1) a detailed description of the available methods, (2) a comparison between these methods, and (3) a decision-making procedure for selecting between these methods. The description and comparison of the methods relies on different criteria: marginals availability, sample size, number of potential attributes that can be handled, population size to generate, possibility of zero-cell problem, and so forth. The advantages and shortcomings of each method are illustrated, and method performance is assessed. The decision-making procedure is carried out through the proposal of a decision tree. Researchers and practitioners have now access to a comprehensive and unified framework to select the appropriate method depending on available data and features of their modeling purposes.

Le projet VibraSimu, financé par la direction scientifique de l'IFSTTAR, a été conduit de 2017 à 2019 par trois laboratoires de l'établissement : le Lepsis, Ease et le LPC. Le projet vise à mesurer les vibrations d'un vélo, à les modéliser et les reproduire sur simulateur immersif et enfin, à en évaluer l'impact sur le ressenti des participants. Le projet offre ainsi une meilleure connaissance des vibrations transmises au vélo et au cycliste lors de la circulation sur différents revêtements et améliore le simulateur vélo de l'institut en produisant les vibrations liées aux irrégularités de la chaussée. Il montre également la limite des dispositifs grand public (smartphones) pour mesurer ces vibrations.

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In a context of decreasing resources and of climate change, lowering road vehicles consumption is a key point to meet CO2 reduction requirements. In addition to car technological advances, eco-driving is part of the solution but the road infrastructure should ensure its development. This work aims to demonstrate that road energy demand and associated pollutant emissions can be reduced by working out minor optimization of road infrastructure itself. For this to happen, a simple eco-driving potential criterion is built upon infrastructure parameters such as slopes and sight distances. This criterion aims to detect Misplaced Speed-sectioning Positions (MSP) with regard to the Starting Point of Deceleration (SPD); with speed-sectioning being the succession of speed changes along a given route. An enhanced energy waste formulation is then developed to quantify the vehicles energy waste due to misplaced road-signs. Thirdly, a traffic simulation constitutes a framework for energy evaluation; considering a full flow of vehicles, based on real traffic data, and by modeling several driver behaviors. Simulation results show that a significant fuel reduction of up to 5.5% can be achieved locally, simply by moving a road sign, for rural areas and without degrading road safety.

La Métropole Rouen Normandie souhaitait concevoir une nouvelle passerelle nécessitant des appuis provisoires en Seine. Aussi a-t-elle sollicité l’Ifsttar pour conduire une étude statistique des données de trajectoires, afin de définir les fuseaux de mobilité des navires en fonction notamment de leur vitesse et de leur gabarit, deux facteurs susceptibles d’avoir un impact sur la manoeuvrabilité des navires. Le traitement des données au format SIA a nécessité de recourir à des outils dédiés aux gros fichiers de données. Puis un modèle de régression linéaire a été retenu pour l’analyse des trajectoires rectilignes hors manoeuvres d’accostage. La détermination d’intervalles de prédiction a permis de délimiter les zones de navigation, et donc de mettre en évidence les surfaces du fleuve aptes à accueillir les appuis provisoires.

Dans cet article, une présentation des propriétés des polynômes de Tchebychev et une formulation dérivée utilisant ces polynômes sont effectuées. La méthode d'identification présentée consiste à appliquer une transformation linéaire sur le système d'équations qui régit le processus. Pour cela, l'opérateur mathématique utilisé s'appuie sur une décomposition du signal dans une base formée de polynômes orthogonaux. Nous montrons que cette projection se comporte comme un filtre passe-bande, de telle sorte qu'une seule opération est nécessaire pour le pré-traitement des données avant le processus d'identification, à savoir choisir la dimension de la base des polynômes Tchebychev. Une identification expérimentale en boucle fermée d'un robot à 2 axes avec cette méthode est effectuée dans une dernière partie. Les résultats obtenus sont comparés et analysés avec d'autres techniques utilisées en robotique.

Eco-driving is an efficient way to preserve energy resources and limit environment impacts. It is first of all a question of driver behaviour and motivation, vehicle characteristics, but infrastructure parameters could favour - or impede- ecodriving. This study aims to qualify this infrastructure influence, for the speed sectioning parameter of roads. A research evaluating the adequacy between speed changes along a route, vehicle dynamics and the road gradient constitute the frame of this work. Indeed this adequacy has been proven to be descriptive of the ecodriving potentiality of a route, as detailed in a previous experimental evaluation in France (Coiret et al [8]). It is reinforced here with the help of experimental evaluation in Bosnia, with a metro-logical reinforcement : differential gps, temporal tagging system at points of interest, roof anemometer for the influence of wind, is now used to have more accurate data. In particular the better altitude measurements increase results quality, with achievable reductions of 5 % of energy consumptions for given route sections with sectioning optimisation (ie : simple speed limit panels repositioning) We have also researched crucial points on how to compare different countries and their legislation, geography, and traffic conditions. Bosnia and Herzegovina and France are in the context, to indicate that an assessment of quality level in eco-driving of the two countries is taken in consideration. Perspectives are given in terms of traffic software generalization of the experimental results and in terms of speed sectioning revisions in order to reduce linked energy losses and CO2 emissions. A route model could then be evaluated, for which speed-sectioning and positioning of amenities (speed bumper, traffic lights) could be optimized in energy use of infrastructure, with a concern not to alter the security features.

The current transport system is not sustainable because of its high consumption of finite resources (mainly oil) and its impact on the environment (air quality, global warming, etc.). In this context, rail has several advantages: lower consumption and emissions than road and air modes, larger passenger flow, etc. That is why, many rail infrastructures are planned in the world. Today, the impact of energy is not taken into account during the project design. At the project phase of new rail infrastructures, it is nowadays important to characterize accurately the energy that will be induced by its operation phase, in addition to other more classical criteria as construction costs and travel time. Current literature consumption models used to estimate railways operation phase are obsolete or not enough accurate for taking into account the newest train or railways technologies. In this paper, an updated model of consumption for high-speed is proposed, based on experimental data obtained from full-scale tests performed on a new high-speed line. The assessment of the model is achieved by identifying train parameters and measured power consumptions for more than one hundred train routes. Perspectives are then discussed to use this updated model for accurately assess the energy impact of future railway infrastructures.

This paper addresses the topic of robot identification. The usual identification method makes use of the inverse dynamic model (IDM) and the least squares (LS) technique while robot is tracking exciting tra- jectories. Assuming an appropriate bandpass filtering, good results can be obtained. However, the users are in doubt whether the columns of the observation matrix (the regressors) are uncorrelated (exo- genous) or correlated (endogenous) with the error terms. The exogeneity condition is rarely verified in a formal way whereas it is a fundamental condition to obtain unbiased LS estimates. In Econometrics, the Durbin-Wu-Hausman test (DWH-test) is a formal statistic for investigating whether the regressors are exogenous or endogenous. However, the DWH-test cannot be straightforwardly used for robot identifi- cation because it is assumed that the set of instruments is valid. In this paper, a Revised DWH-test suitable for robot identification is proposed. The revised DWH-test validates/invalidates the instruments chosen by the user and validates the exogeneity assumption through the calculation of the QR factor- ization of the augmented observation matrix combined with a F-test if required. The experimental results obtained with a 6 degrees-of-freedom (DOF) industrial robot validate the proposed statistic.

In accordance with the environmental concerns that national policies still address throughout the world, railways have been extensively studied to provide quantified indicators for assessing construction/operations practices. It is essential to take energy consumption, into account since energy can be measured worldwide, in addition to constituting a global environmental load that is time-limited as regards resource availability and known as a discriminating criterion in comparing transport infrastructure. This article introduces an innovative, generic and systemic method dedicated to determining the energy consumption of a railway line during the pre-project phase by taking into account the complete life cycle of the rail infrastructure, including construction, maintenance and operations. The method developed (called PEAM ) focuses on assessing project variants during the design stage and therefore integrates both the geometric longitudinal constraints of the line and the thicknesses/volumes over the entire itinerary as design parameters for input into the various construction scenarios. PEAM combines methodologies stemming from life cycle assessment with a consumption model derived from physical modeling. The models associated with this method are then applied to study the energy consumption of a new high-speed line located in France that also has major implications for the European connections currently under investigation as well. Two project variants are compared in terms of total energy for a 50-year service life and a given characteristic rail traffic, including passenger and freight flows. Results obtained reveal a 30% difference between the two variants, which prior to applying PEAM were considered to be relatively similar.

The current transport system is not sustainable because of its high consumption of finite resources (mainly oil) and its impact on the environment (air quality, global warming, etc.). In this context, rail has several advantages: lower consumption and emissions than road and air modes, larger passenger flow, etc. That is why, many rail infrastructures are planned in the world. Today, the impact of energy is not taken into account during the project design. At the project phase of new rail infrastructures, it is nowadays important to characterize accurately the energy that will be induced by its operation phase, in addition to other more classical criteria as construction costs and travel time. Current literature consumption models used to estimate railways operation phase are obsolete or not enough accurate for taking into account the newest train or railways technologies. In this paper, an updated model of consumption for high-speed is proposed, based on experimental data obtained from full-scale tests performed on a new high-speed line. The assessment of the model is achieved by identifying train parameters and measured power consumptions for more than one hundred train routes. Perspectives are then discussed to use this updated model for accurately assess the energy impact of future railway infrastructures.

Les métros automatiques, sans conducteurs, sont en déploiement important depuis des décennies et offrent de hauts niveaux de service et de sécurité. S’affranchir du facteur humain peut en effet augmenter ces niveaux en exploitation courante mais des protocoles robustes de commande sont alors requis pour pallier l’absence des qualités humaines d’anticipation et d’adaptation en situations exceptionnelles. De tels protocoles, dits d’anti‐collision, sont généralement basés sur une performance minimale de freinage garantie associée à un découpage de l’infrastructure en cantons, fixes ou mobiles, assurant qu’il ne puisse y avoir simultanément plus d’un véhicule sur le même canton. En particulier, un système de métro automatique sur pneu est présenté dans cet article. Des résultats d’essais de freinage de rames montrent l’efficacité de traitements visant à améliorer l’adhérence pneumatique/piste de roulement. L’entretien des pistes pour maintenir un bon niveau de freinage est discuté pour les techniques courantes de striage et de grenaillage des pistes. Enfin, une méthodologie pour permettre le suivi des pistes en temps et en espace est proposée. Elle inclut la sélection et l’emploi de matériels d’évaluation de l’adhérence issus du domaine routier.

Rouen métropole a sollicité les capacités de l'Ifsttar dans le domaine du traitement du signal appliqué à l'usage des infrastructures à travers un courriel envoyé le 1er mars 2017 par M Toynan, responsable du service Ouvrage d'art de la métropole de Rouen, à MM Coiret et Vandanjon, chercheurs à l'Ifsttar. Cette sollicitation concerne un ouvrage en projet pour le franchissement de la Seine. L'ouvrage sera de type léger, sous la forme d'une passerelle dédiée aux modes doux (cycles, piétons). Il complètera l'offre de franchissement existante et reliera efficacement des pôles générateurs de déplacements dans l'agglomération, et notamment l'Ecoquartier Luciline en cours de réalisation en rive droite et l'Ecoquartier Flaubert en projet en rive gauche dans le cadre du projet global Seine Cité. L'ouvrage est donc envisagé dans le secteur Ouest de l'agglomération rouennaise, entre les ponts Guillaume Le Conquérant et Gustave Flaubert, soit en traverse de la partie de Seine accueillant régulièrement la grande Armada. Les appuis principaux de la structure seraient situés dans l'alignement des hangars existants. La structure provisoire dite > sera déconstruite préalablement aux travaux de passerelle. A ce jour, il n'est pas envisagé d'implanter d'appui définitif en Seine. Néanmoins, le recours à des appuis intermédiaires en phase réalisation semble incontournable. De même, la définition d'un gabarit de passe navigable influe sur la définition de la limite basse d'intrados d'ouvrage et donc sur la définition des accès. Seule une connaissance plus précise des trajectoires fluviales entre le Pont Guillaume le Conquérant en amont et le Pont Flaubert en aval permettra donc de gagner en précision sur la définition des implantations possibles d'appuis provisoires puis sur la définition du gabarit fluvial définitif. À cet effet, l'Ifsttar a été sollicité pour une étude statistique de trajectoire de navires, selon un cahier des charges qui est donné en annexe au présent document. L'Ifsttar a répondu à ce cahier des charges en rédigeant une proposition technique, également en annexe à ce document, dont le produit est un rapport d'étude sur les trajectoires fluviales sur la section considérée. Une réunion de lancement a eu lieu le 11 mai 2017 dans les locaux de Rouen métropole. Ce document est la troisième version de ce rapport d'étude. Une première version a été envoyée le 17 juin afin d'échanger avec la Métropole Rouen Normandie. Ce document a été le support d'une réunion téléphonique avec la métropole de Rouen le 27 juin afin, notamment, de préparer une réunion entre la métropole et le grand port maritime de Rouen. Nous avons abouti à une deuxième version envoyée le 3 juillet 2017 afin de fournir des données opérationnelles pour la métropole. Suite à des relectures internes, nous avons modifié cette deuxième version en améliorant sa forme afin d'aboutir à cette version qui est remise lors de la réunion de présentation des résultats du 11 juillet 2017. Ce rapport est découpé en 10 chapitres. Tout d'abord, la structure des données, que nous avons obtenues par le port maritime, est expliquée. Les grandes étapes du traitement de ces données sont présentées dans le chapitre suivant. Puis, les résultats de ce traitement sont affichées sous forme de graphiques pour chaque trimestre de l'année 2016 dans les chapitres 4 à 8. Enfin, les deux dernier chapitres discutent les résultats et conclut le rapport.

In railway planning, the timetabling step needs, as input, the train running times, which are calculated from a train dynamic model. Usually, this model determines the most energy-efficient train trajectory for a predefined time. However, this time may not correspond to the timetable-makers' needs. They should have the choice among a set of solutions, more or less energy-consuming. This study proposes a method capable of producing a set of alternative running times with the associated mechanical energy required. To this end, the authors' contribution is to set up an efficient evolutionary multi-objective algorithm builds a set of well-spread and diversified solutions which approximate a Pareto front. The solutions are all compromises between running time and energy-consumption, the two minimisation objectives concurrently optimised. Given that an evolutionary algorithm is strongly dependent on the initialisation phase, the efficiency of the algorithm is improved through a specific and original mechanism connecting multiple initialisations in cascade in order to accelerate the convergence towards the best solutions. A set of results obtained on randomly-generated instances is analysed and discussed.

Le fil conducteur de ma recherche est l'application des techniques robotiques en identification des modèles inverses aux systèmes de transport routier et ferroviaire. Mes compétences scientifiques sont dans le domaine des mathématiques appliquées : statistiques, analyse numérique matricielle, théorie de la viabilité. Travaillant dans un organisme de recherches finalisées, ces compétences ont été mises en oeuvre pour résoudre des questions pratiques - souleÎes par les chantiers du génie civil : estimation du torseur des efforts de contact lors du compactage des enrobés, évaluation de différents systèmes de malaxage des bétons [10] ; - provenant de la sécurité routière : mesures de la courbe reliant le taux de glissement au frottement pneumatique/chaussée d'un Îhicule routier en freinage [1], évaluation de l'état d'un Îhicule en conduite apaisée[9], - en écoconception : évaluation de la consommation des trains circulant sur une ligne à grande vitesse [2], établissement des fiches horaires pour les conducteurs (article accepté). Ces problèmes pratiques - ont nécessité des expérimentations de grandes ampleurs : 50 % de mes publications sont liés à des expérimentations que j'ai souvent organisées ; - ont dépassé mon champ disciplinaire : tous mes travaux sont effectués en collaboration avec d'autres laboratoires et avec des industriels. D'un point de vue théorique, j'ai contribué à l'établissement des méthodes d'identifications : IDIM-LS, IDIM-IV, DIDIM. ([3, 5, 6, 7, 4, 8]). Une contribution théorique complètement différente et fortuite est l'introduction des concepts issus de la théorie de la viabilité en sécurité routière [9]. Mon activité de recherche en terme d'encadrement et de publications. Publications : 10 revues, 1 brevet (français et mondial), 29 congrès internationaux sur article dont 22 Ifac-Ieee, 11 congrès internationaux sur résumé, 5 revues techniques francophones, 7 congrès francophones. Encadrement de thèses et de post-doctorant : 1,88 sur 4 thèses (3 Bourses Cifre, 1/2 Bourse Région, 1/2 Bourse Ifsttar), 1 post-doctorant (financé sur projet Européen).

Le point de départ de notre recherche était la comparaison environnementale de différentes techniques de construction d'infrastructure de transport. Ce travail est matérialisé par le logiciel Ecorce. Il s'agissait de sélectionner et d'améliorer les techniques de construction pour réduire les impacts environnementaux. Cependant, les impacts environnementaux d'une infrastructure de transport sont, pour des critères comme les GES ou l'énergie, imputables pour une grande partie à la phase d'usage. L'idée initiale de notre recherche fut donc d'évaluer et de proposer des solutions afin de limiter les impacts de la phase d'usage dès la conception du projet par l'optimisation des matériaux ou des tracés. Aborder la phase d'usage étend considérablement les domaines à étudier. Pour arriver à des résultats concrets, nous avons restreint notre champ d'investigation à deux critères : les GES et l'énergie. Par ailleurs, nous avons travaillé en collaboration : avec la SNCF réseau sur la partie ferroviaire, avec le Laboratoire Transport et Environnement sur la partie routière. Ainsi, dans le domaine ferroviaire, nous avons proposé une méthodologie d'évaluation appelée PEAM (Project Energy Assessment Method) que nous avons appliquée pour évaluer et comparer deux tracés sur le projet de ligne à grande vitesse Montpellier-Perpignan. Dans le domaine ferroviaire, nous sommes allés au bout des objectifs initiaux du livrable, car nous avons aussi considéré la ligne classique existante, nous nous sommes donc situés au niveau d'un réseau. Dans le domaine routier, nous avons proposé une méthodologie appelée Sloop (Slope optimisation) afin d'optimiser le profil longitudinal d'un tracé routier pour limiter l'énergie ou les émission de GES pendant les phases de construction, de maintenance et d'usage. Nous l'avons appliqué sur un projet récent de modification du tracé de la RN7 afin d'évaluer son potentiel. Ainsi, sur ce cas, nous avons montré que nous pouvions baisser de 10% les émissions de GES en phase d'usage en proposant un profil longitudinal optimisé et réaliste au regard des critères de conception routière. Nous avons également contribué à démontrer l'influence de la texture sur la consommation de carburant en étudiant l'impact de la résistance au roulement du reÐtement de chaussée. Ceci ouvre des perspectives importantes concernant la gestion des réseaux d'infrastructure. En effet, certaines techniques bas coût comme les enduits ont des macrotextures importantes qui pourraient être à l'origine de surconsommation. Alors que le domaine routier était notre domaine de prédilection, nous sommes allés moins loin que dans le domaine ferroviaire en n'atteignant pas l'échelle du réseau comme le titre initial du livrable le présuppose. Cela tient à la différence de culture entre les deux domaines. Le propriétaire de lgv tient compte explicitement de l'énergie qu'il va facturer à l'entreprise ferroviaire. Le propriétaire d'un réseau routier n'est pas dans cette situation. Il a, donc, été, pour nous, plus facile de susciter des collaborations avec des entreprises du domaine ferroviaire que dans le domaine routier. Cependant, nos résultats récents nous rendent optimistes pour nouer de nouvelles collaborations dans ce secteur. Nous avons proposé une suite à ce travail pour le contrat d'objectif et de performance 2017-2021. Cette proposition a été validée par l'Ifsttar et ses tutelles. Nous utiliserons nos acquis concernant l'évaluation de la phase d'usage pour orienter nos travaux vers l'écoexploitation des infrastructures de transport. Il s'agira de proposer un outil d'évaluation des impacts environnementaux qui prendra en compte la phase d'usage ce qui permettra de synthétiser nos résultats et de les proposer via un logiciel adapté à la profession. Nous travaillerons également sur la potentialité d'éco-conduite des infrastructures routières selon l'adéquation entre tracé et vitesse d'usage à travers une thèse qui a commencé fin 2016 en cotutelle avec l'université de Sarajevo. Nous continuerons à travailler sur la résistance au roulement et sur l'influence des paramètres géométrique des tracés sur la consommation au sein du projet Danois Rose. Nous avons prévu une ouverture au mode doux en étudiant l'usage des pistes cyclables en développant un appareil permettant de mesurer la « cyclabilité » des itinéraires à Îlo, la « cyclabilité » étant la mesure de l'énergie d'usage. Lors de la prise en compte de la phase d'usage, nous avons concentré nos travaux sur deux critères : les GES et l'énergie. Sans se disperser, nous nous intéresserons progressivement à d'autres indicateurs comme les émissions de particules fines.Enfin, nous sommes, actuellement, limités dans nos évaluations par nos hypothèses simplistes sur le trafic. Nous devrons monter des collaborations afin de construire différents scénarios d'évolution permettant de fournir des évaluations plus riches tenant compte, notamment, de l'arriÎe du Îhicule autonome.

Nova'TP, commission TP de NOVABUILD, a initié un groupe de travail visant à favoriser l'innovation dans les marchés publics de travaux, grâce à l'élaboration de cahier des charges décrivant les performances attendues plutôt que les moyens de les atteindre. Cette démarche s'est appuyée sur l'exemple concret du choix des matériaux des pistes cyclables, qui sont intégrées à la plupart des aménagements réalisés sur l'espace public. La première étape du projet a consisté à définir les critères objectifs de performance de ces matériaux, afin de répondre aux enjeux de confort, de développement durable, de coût... exprimés par les maitres d'ouvrage. Sur certains critères, comme le confort, l'absence de référentiel existant pour les infrastructures cyclables, nous a conduit à développer une démarche innovante, en adaptant l'usage du Vel'Audit (Îlo instrumenté, prévu initialement pour l'inspection à haut rendement d'aménagements cyclables). Les matériaux déjà couramment utilisés pour ce type d'infrastructure ont été caractérisés selon ces critères. Ces données ont ensuite été regroupées dans une application, développée pour faciliter l'analyse et la comparaison des offres par les maîtres d'ouvrage. Cette application permet de comparer des matériaux conventionnels entre eux ou avec des matériaux innovants sous un aspect performentiel. Ce logiciel d'aide à la décision a été testé par Nantes Métropole sur plusieurs opérations d'aménagement, pour Îrifier sa pertinence et proposer certaines évolutions.

Les collectivités françaises développent de plus en plus d'aménagement cyclables, et il apparaît donc plus d'attentes concernant la sécurité de ces aménagements, leur confort, leur durabilité, leur gestion et entretien... Si pour le réseau routier général, les maîtres d'ouvrages disposent d'outils d'aide à la décision, basés sur des critères tels que la sécurité, la mobilité, l'environnement et le coût, les voies cyclables ne sont que partiellement concernées par ces outils. Ce travail vise à répondre aux attentes des gestionnaires de réseaux cyclables et a été réalisé dans le cadre du groupe de travail « Nova-TP » sur l'innovation dans les transports. En première partie de ce travail, L'outil Vel'audit est présenté. DériÎ des outils routiers, Vel'Audit est un Îlo instrumenté qui permet de réaliser des releÎs d'images ensuite exploitables à l'aide du logiciel IREVE. Ce diagnostic permet à la fois de caractériser l'infrastructure et d'identifier des défauts de cyclabilité. Vél'audit dispose aussi d'une centrale inertielle mesurant les vibrations subies par le Îlo et conduisant au calcul d'un indicateur confort indexé à la vitesse d'avancement. Pour l'aspect sécurité, le SRT (Skid Resistance Tester) est ensuite présenté, comme un des moyens de mesure de l'adhérence exploité pour les routes et pouvant être directement transposé aux pistes cyclables. Des essais de validité sur piste cyclable sont ensuite discutés et, en perspectives, le développement d'un matériel utilisable continûment sur itinéraire, inspiré du Grip-Tester, est envisagé en prolongement des mesures ponctuelles du SRT. Ainsi différentes techniques d'auscultations routières éprouÎes peuvent répondre aux besoins émergents des gestionnaires d'infrastructures cyclables, tout en s'adaptant aux caractéristiques de ces déplacements cyclables. Ces transpositions sont encore peu investie alors même que les besoins existent et qu'en finalité cela pourrait aboutir à la construction d'un indice de qualité cyclable (IQCy) à l'image de l'IQRN routier.

The energy associated with the use of road infrastructure exceeds in few years the energy needed for its construction. The link between infrastructure and use energy has not been, however, studied in depth, particularly as the legitimate transport societal expectations are related to efficiency and safety. However, we can consider reducing the energy use by working out minor optimizations of the road infrastructure itself, which is a major challenge in a context of overall decrease of resources and increasing pressures on the environment. Experimental work is carried out here to develop one of these optimizations by improving the eco-driving potential of roads. It is based on the adequacy between vehicles dynamics, the road longitudinal profile and the speed sectioning of the infrastructure. This sectioning corresponds to the succession of speed limitations (road signs, roundabouts, intersections ...). It may allow drivers to eco-drive or not, depending on dynamics, slopes, and secondary parameters as driver reaction time or distance of visibility. Optimal speed sectioning aims to limit the mechanical braking needed by potential energy reduction, due to slopes, which can be encountered simultaneously with the needed kinetic energy reduction. Evaluation has been made on actual road sections, while recording both vehicle dynamics, driver commands, road signs positions and road longitudinal profile. Results show that energy consumption of vehicles approaching a speed reduction sign can be reduced by moving backward this sign of about 700 meters, without penalizing the primary safety function. The associated gain, for this optimization, has been evaluated to 14 liters of fuel per day for one of the experimental sites, considering traffic data. Application of this method on a network could then lead to considerable energy saving by allowing eco-driving.

This paper deals with the identification of physical parameters of a one-degree-of-freedom electromechanical system that operates in closed loop. Two models are considered: the inverse dynamic model which is linear in relation to the physical parameters to be identified and the direct dynamic model which is linear in relation to a nonlinear combination of the physical parameters. Three methods are considered and compared: the traditional method which makes use of the inverse dynamic model, tailormade data prefiltering and the least-squares method, an instrumental variable approach which makes use of the direct and inverse dynamic models and another instrumental variable approach which makes use of the direct dynamic model only. The experimental results show that the instrumental variable method based on the use of the inverse and direct dynamic models seems to be more appropriate than the two others because it is robust against noise and the physical parameters are directly identified.

This paper addresses the important topic of joint flexibility identification. Three dynamic models depending on measurements availability are compared. The parameters are estimated by using the ordinary least squares of an over linear system obtained from the sampling of the dynamic model along a closed loop tracking trajectory. An experimental setup exhibits the experimental identification results.

Current transport systems are not likely to be sustainable, since energy resources may be less accessible, facing a rapidly growing demand and because of environmental constrains. In this context a great interest arose for sharing environmental assessment practices between infrastructures owners and researchers. For this present work a partnership between RFF and Ifsttar was decided to study environmental effects and energy consumption for railways life cycle. It paves the way to a full life cycle analysis (LCA) for environmental burdens of railway infrastructures and aims at identifying the best design practices at the project level related to environmental criteria. This LCA takes into account earthwork, railway structure and the operation phase, i.e., the analysis performed is based on the estimation of energy consumptions due to construction, maintenance and on the traffic. Results of this work could enhance practices for environment preservation for the plan of building 4000 kilometres of new high-speed railways, decided in the French National Transport infrastructure scheme. Applying LCA to the project phase is a rather new approach. It requires defining a global functional unit as a basic hypothesis of any study, different from the previous studies. Then, the lifecycle subsystems are successively investigated (construction, maintenance and use) to determine the best way for project Functional Unit definition and further assessment method application.

Viability theory proposes geometric metaphors in addition to classical ordinary differential equation analysis. In this paper, advantages of applying viability theory to road safety domain are presented. The exact issue is to determine if, from an initial state of a vehicle/road/driver system, a soft controls strategy is compatible with a safe driving sequence. The case of a car negotiating a curve is considered. The application of the viability theory to this issue offers the advantage to avoid classical full computing of the system. Instead of that, it consists on verifying that the states and the controls belong to a subset called the viability kernel. The construction and the use of the viability kernel for a vehicle system dynamic is proposed by using support vector machines algorithm. Then, the applicability of this theory is demonstrated through experimental tests. This innovative application of the viability theory to vehicle dynamics with road safety concerns could benefit to robust embedded warning systems.

This paper deals with the important topic of rigid industrial robots identification. The usual identification method is based on the use of the inverse dynamic model and the least-squares technique. In order to obtain good results, a well-tuned derivative bandpass filtering of joint positions is needed to calculate the joint velocities and accelerations. However, we can doubt whether the bandpass filter is well-tuned or not. Another approach is the instrumental variable (IV) method which is robust to data filtering and which is statistically optimal. In this paper, an IV approach relevant for identification of rigid industrial robots is introduced. The set of instruments is the inverse dynamic model built from simulated data which are calculated from the simulation of the direct dynamic model. The simulation assumes the same reference trajectories and the same control structure for both the actual and the simulated robot and is based on the previous IV estimates. Furthermore, to obtain a rapid convergence, the gains of the simulated controller are updated according to IV estimates. Thus, the proposed approach validates the inverse and direct dynamic models simultaneously and is not sensitive to initial conditions. The experimental results obtained with a 2 degrees of freedom (DOF) planar prototype and with a 6 DOF industrial robot show the effectiveness of our approach: it is possible to identify 60 parameters in 3 iterations and in 11 s.

This paper deals with the important topic of industrial robot identification. The usual identification method is based on the inverse dynamic identification model and the least squares technique. This method has been successfully applied on several industrial robots. Good results can be obtained, provided a well tuned derivative band-pass filtering of joint positions is used to calculate the joint velocities and accelerations. However, one cannot be sure whether or not the band-pass filtering is well tuned. An alternative is the instrumental variable (IV) method, which is robust to data filtering and is statistically optimal. In this paper, a generic IV approach suitable for robot identification is proposed. The instrument set is the inverse dynamic model built from simulated data calculated from simulation of the direct dynamic model. The simulation is based on previous estimates and assumes the same reference trajectories and the same control structure for both actual and simulated robots. Finally, gains of the simulated controller are updated according to IV estimates to obtain a valid instrument set at each step of the algorithm. The proposed approach validates the inverse and direct dynamic models simultaneously, is not sensitive to initial conditions, and converges rapidly. Experimental results obtained on a six-degrees-of-freedom industrial robot show the effectiveness of this approach: 60 dynamic parameters are identified in three itérations.

In the hardening energy context, the transport sector which constitutes a large worldwide energy demand has to be improving for decrease energy demand and global warming impacts. In a controversial situation where subsists an increasing demand for long-distance and high-speed travels, high-speed trains offer many advantages, as consuming significantly less energy than road or air transports. At the project phase of new rail infrastructures, it is nowadays important to characterize accurately the energy that will be induced by its operation phase, in addition to other more classical criteria as construction costs and travel time. Current literature consumption models used to estimate railways operation phase are obsolete or not enough accurate for taking into account the newest train or railways technologies. In this paper, an updated model of consumption for high-speed is proposed, based on experimental data obtained from full-scale tests performed on a new high-speed line. The assessment of the model is achieved by identifying train parameters and measured power consumptions for more than one hundred train routes. Perspectives are then discussed to use this updated model for accurately assess the energy impact of future railway infrastructures.

This paper deals with the topic of industrial robots identification. The usual identification method is based on the use of the inverse dynamic model (IDM) and least squares (LS) technique. Good results can be obtained provided that a well-tuned bandpass filtering is used. However, we are always in doubt if regressors are exogenous i.e. statistically uncorrelated with error terms. Surprisingly, in papers dealing with identification of real-world systems, exogeneity assumption is never verified whereas it is a fundamental condition to obtain unbiased estimates. In Econometrics, the Durbin-Wu-Hausman test (DWH-test) is a theoretical method for investigating whether regressors are exogenous or not. The DWH-test makes of the Two Stage Lesat Squares estimator (2SLS) and an augmented LS regression. However, this test cannot be used as is for robots identification: instruments set is supposed to be valid and restrictive statistical assumptions are made while they are quite implausible in practice. In this paper, we aim at bridging the gap between Econometrics and Control engineering practices by introducing a revisited version relevant for robots identification. An experimental validation performed on a 2 degrees of freedom (DOF) robot shows the effectiveness and the usefulness of this revisited DWH-test.

This paper deals with the topic of robots dynamics identification. In this paper, we focus on the instrumental variable (IV) technique. For robots, the set of instruments is the inverse dynamic model built from simulated data which are calculated from the integration of the direct dynamic model, assuming the same reference trajectories and the same control law structure for both actual and simulated robots. The integration of the direct dynamic model is based on previous IV estimates. This defines an iterative algorithm. Furthermore, gains of the simulated controller are updated to get a fast convergence. Experimental results obtained on a six degrees of freedom robot manufactured by Stäubli show the effectiveness of our approach: 60 dynamic parameters are estimated in only two iterations.

Offline robot dynamic identification methods are mostly based on the use of the inverse dynamic model, which is linear with respect to the dynamic parameters. This model is sampled while the robot is tracking reference trajectories that excite the system dynamics. This allows using linear least-squares techniques to estimate the parameters. The efficiency of this method has been proved through the experimental identification of many prototypes and industrial robots. However, this method requires the joint force/torque and position measurements and the estimate of the joint velocity and acceleration, through the bandpass filtering of the joint position at high sampling rates. The proposed new method called DIDIM requires only the joint force/torque measurement, which avoids the calculation of the velocity and acceleration by bandpass filtering of the measured position. It is a closed-loop output error method where the usual joint position output is replaced by the joint force/torque. It is based on a closed-loop simulation of the robot using the direct dynamic model, the same structure of the control law, and the same reference trajectory for both the actual and the simulated robot. The optimal parameters minimize the 2-norm of the error between the actual force/torque and the simulated force/torque. This is a nonlinear least-squares problem which is dramatically simplified using the inverse dynamic model to obtain an analytical expression of the simulated force/torque, linear in the parameters. A validation experiment on a two degree-of-freedom direct drive rigid robot shows that the new method is efficient.

Viability theory proposes geometric metaphors in addition to classical ordinary differential equation analysis. This theory is applied on a vehicle cornering. The issue is to determine if a state of the system is compatible with a soft controls strategy which leads the car to the end of the corner. The viability theory offers tools which enable to answer to this question without computing in real time these controls. The issue resumes to verify that this state belongs to a set called the viability kernel. The construction and the use of the viability kernel for a vehicle system dynamic is proposed by using Support Vector Machines algorithm. The applicability of this theory is demonstrated through experimental tests. It is the first time that the viability theory is applied to vehicle dynamics with road safety concerns.

This paper deals with joint stiffness identification with a new Closed-Loop Output Error (CLOE) method which minimizes the quadratic error between the actual motor force/torque and the simulated one. This method is based on the DIDIM (Direct and Inverse Identification Model) procedure which has been validated on rigid robots and which is now applied to a flexible joint robot. DIDIM method requires a gain updating in the simulated robot in order to keep the bandwidth of the rigid controlled degree of freedom (dof ) and to keep the natural frequency of the flexible dof, close to the actual ones, at each step of the recursive Gauss Newton non linear programming algorithm. This gain updating requires a first step of estimating the natural frequency of the flexible dof before applying DIDIM method in a second step. An experimental setup exhibits identification results and shows the effectiveness of our approach.

Ce papier présente une nouvelle méthode à erreur de sortie en deux étapes pour l'identification en boucle fermée des paramètres inertiels, de frottements et de raideur d'un axe de robot avec flexibilité articulaire localisée. Cette méthode utilise uniquement l'effort et la position du moteur, sans aucune mesure de flexibilité. La première étape identifie la fréquence du mode rigide asservi et la fréquence du mode flexible à entrée bloquée, en utilisant un modèle haute fréquence double intégrateur du robot. L'identification utilise une méthode à erreur de sortie sur la position du moteur. Ces deux paramètres de fréquence optimaux sont ensuite utilisés dans la deuxième étape pour l'identification des paramètres dynamiques du robot par une méthode à erreur de sortie sur l'effort moteur. Cette méthode récente (DIDIM) qui utilise les modèles d'identification directe et inverse du robot permet d'obtenir une convergence des paramètres très rapide et insensible aux conditions initiales. Une validation expérimentale sur un robot un axe montre l'efficacité de la nouvelle méthode comparée à deux méthodes à erreur de sortie classiques.

This paper addresses the important topic of joint flexibility identification. Three dynamic models depending on measurements availability are compared. The parameters are estimated by using the ordinary least squares of an over linear system obtained from the sampling of the dynamic model along a closed loop tracking trajectory. An experimental setup exhibits the experimental identification results.

This paper deals with joint stiffness identification with only actual motor force/torque data instead of motor and load positions. The parameters are estimated by using the DIDIM method which needs only input data. This method was previously validated on a 6 DOF rigid robot and is now extended to flexible systems. The criterion to be minimized is the quadratic error between the measured actual motor force/torque and the simulated one. The optimal parameters are calculated with the Nelder - Mead simplex algorithm. An experimental setup exhibits the experimental identification results and shows the effectiveness of our approach.

Given a rooted, binary phylogenetic network and a rooted, binary phylogenetic tree, can the tree be embedded into the network? This problem, called \textsc{Tree Containment}, arises when validating networks constructed by phylogenetic inference methods.We present the first algorithm for (rooted) \textsc{Tree Containment} using the treewidth $t$ of the input network $N$ as parameter, showing that the problem can be solved in $2^{O(t^2)}\cdot|N|$ time and space.

We consider the use of the spatio-temporal sample autocorrelation matrix in order to determine whether the signals received by a distributed antenna system are spatially correlated. The asymptotic behavior of linear spectral statistics built from this matrix is studied, assuming that (i) the number of antennas, (ii) the sample size and (iii) the number of tested time lags all converge to infinity. In this asymptotic regime, linear spectral statistics of the spatiotemporal sample correlation matrix are shown to be asymptotically equivalent to the corresponding functional average with respect to a Marchenko-Pastur distribution. This means that the eigenvalue distribution of the original sample autocorrelation matrix essentially behaves as a sample covariance matrix of spatio-temporal white noise with equivalent dimensions. This result turns out to be useful in order to address the problem of detecting the presence of wideband directional signals with a number of uncalibrated receivers distributed over a large area.

Dans cet article, nous étudions un test de corrélation pour les composantes d'une série temporelle gaussienne complexe multivariée de dimension M. Une statistique de test basée sur un estimateur empirique du maximum de la cohérence spectrale est proposée, et son risque de 1ère espèce est étudié dans un régime asymptotique des grandes dimensions où M → ∞. Nous donnons également quelques résultats numériques illustrant les performances de la statistique proposée dans divers scénarios.

We introduce the French Land cover from Aerospace ImageRy (FLAIR), an extensive dataset from the French National Institute of Geographical and Forest Information (IGN) that provides a unique and rich resource for large-scale geospatial analysis. FLAIR contains high-resolution aerial imagery with a ground sample distance of 20 cm and over 20 billion individually labeled pixels for precise landcover classification. The dataset also integrates temporal and spectral data from optical satellite time series. FLAIR thus combines data with varying spatial, spectral, and temporal resolutions across over 817 km2 of acquisitions representing the full landscape diversity of France. This diversity makes FLAIR a valuable resource for the development and evaluation of novel methods for large-scale land-cover semantic segmentation and raises significant challenges in terms of computer vision, data fusion, and geospatial analysis. We also provide powerful uni- and multi-sensor baseline models that can be employed to assess algorithm’s performance and for downstream applications. Through its extent and the quality of its annotation, FLAIR aims to spur improvements in monitoring and understanding key anthropogenic development indicators such as urban growth, deforestation, and soil artificialization. Dataset and codes can be accessed at https://ignf.github.io/FLAIR

We propose and study a method called FLOT that estimates scene flow on point clouds. We start the design of FLOT by noticing that scene flow estimation on point clouds reduces to estimating a permutation matrix in a perfect world. Inspired by recent works on graph matching, we build a method to find these correspondences by borrowing tools from optimal transport. Then, we relax the transport constraints to take into account real-world imperfections. The transport cost between two points is given by the pairwise similarity between deep features extracted by a neural network trained under full supervision using synthetic datasets. Our main finding is that FLOT can perform as well as the best existing methods on synthetic and real-world datasets while requiring much less parameters and without using multiscale analysis. Our second finding is that, on the training datasets considered, most of the performance can be explained by the learned transport cost. This yields a simpler method, FLOT0, which is obtained using a particular choice of optimal transport parameters and performs nearly as well as FLOT.

Composed Image Retrieval (CoIR) has recently gained popularity as a task that considers both text and image queries together, to search for relevant images in a database. Most CoIR approaches require manually annotated datasets, comprising image-text-image triplets, where the text describes a modification from the query image to the target image. However, manual curation of CoIR triplets is expensive and prevents scalability. In this work, we instead propose a scalable automatic dataset creation methodology that generates triplets given video-caption pairs, while also expanding the scope of the task to include composed video retrieval (CoVR). To this end, we mine paired videos with a similar caption from a large database, and leverage a large language model to generate the corresponding modification text. Applying this methodology to the extensive WebVid2M collection, we automatically construct our WebVid-CoVR dataset, resulting in 1.6 million triplets. Moreover, we introduce a new benchmark for CoVR with a manually annotated evaluation set, along with baseline results. Our experiments further demonstrate that training a CoVR model on our dataset effectively transfers to CoIR, leading to improved state-of-the-art performance in the zero-shot setup on both the CIRR and FashionIQ benchmarks. Our code, datasets, and models are publicly available at https://imagine.enpc.fr/~ventural/covr.

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Current approaches to generic segmentation start by creating a hierarchy of nested image partitions and then specifying a segmentation from it. Our first contribution is to describe several ways, most of them new, for specifying segmentations using the hierarchy elements. Then, we consider the best hierarchy-induced segmentation specified by a limited number of hierarchy elements. We focus on a common quality measure for binary segmentations, the Jaccard index (also known as IoU). Optimizing the Jaccard index is highly non-trivial, and yet we propose an efficient approach for doing exactly that. This way we get algorithm-independent upper bounds on the quality of any segmentation created from the hierarchy. We found that the obtainable segmentation quality varies significantly depending on the way that the segments are specified by the hierarchy elements, and that representing a segmentation with only a few hierarchy elements is often possible. (Code is available).

The past years have seen a great progress of deep generative models, including Generative Adversarial Networks (GANs). Notably, they can synthesize high-resolution images, sometimes indistinguishable from real images. Deep generative models were also at the root of empirical successes such as music generation or molecular discovery. However, we lack a fundamental understanding of the capabilities and limitations of deep generative models. In this thesis, we first characterize a model misspecification of generative models with connected output distributions, such as GANs or normalizing flows. Indeed, such models can not perfectly fit a target distribution composed of several disconnected modes. We analyse theoretically their best achievable performance in the setting of disconnected target distribution, and which geometrical structure can allow them to achieve best performance. Moreover, we propose methods that the performance of GANs by making them more amenable for disconnected data modelling.In the second part of the thesis, we aim to improve image editing techniques thanks to deep generative models. First, we leverage a pre-trained unconditional generative model and show that it can perform a wide range of image editing tasks without re-training. Second, we build on adversarial learning to improve virtual try-on models, which consist in replacing the clothing item on an image of a person.

The last decade has seen the resolution of several basic NP-complete problems in geometric combinatorial optimisation-interestingly, all with the same algorithm: local search. This includes the existence of polynomial-time approximation schemes (PTASs) for hitting set, set cover, dominating set, independent set, and other problems for some basic geometric objects. More precisely, it was shown that for many of these problems, local search with radius λ gives a (1 + O(λ-1 2))approximation with running time n O(λ). Setting λ = Θ (ε-2) yields a PTAS with a running time of n O(ε-2). On the other hand, hardness results suggest that there do not exist PTASs for these problems with running time poly(n) • f (ε) for any arbitrary computable f. Thus the main question left open in previous work is in improving the exponent of n to o(ε-2). Our main result is that the approximation guarantee of the standard local search algorithm cannot be improved for any of these problems, which we show by constructing instances with poor "locally optimal solutions". The key ingredient, of independent interest, is a new lower bound on locally expanding planar graphs. Our construction extends to other graph families with small separators.

A graph is called odd (respectively, even) if every vertex has odd (respectively, even) degree. Gallai proved that every graph can be partitioned into two even induced subgraphs, or into an odd and an even induced subgraph. We refer to a partition into odd subgraphs as an odd colouring of G. Scott [Graphs and Combinatorics, 2001] proved that a graph admits an odd colouring if and only if it has an even number of vertices. We say that a graph G is k-odd colourable if it can be partitioned into at most k odd induced subgraphs. We initiate the systematic study of odd colouring and odd chromatic number of graph classes. In particular, we consider for a number of classes whether they have bounded odd chromatic number. Our main results are that interval graphs, graphs of bounded modular-width and graphs of bounded maximum degree all have bounded odd chromatic number.

Consider a graph drawn on a surface (for example, the plane minus a finite set of obstacle points), possibly with crossings. We provide an algorithm to decide whether such a drawing can be untangled, namely, if one can slide the vertices and edges of the graph on the surface (avoiding the obstacles) to remove all crossings; in other words, whether the drawing is homotopic to an embedding. While the problem boils down to planarity testing when the surface is the sphere or the disk (or equivalently the plane without any obstacle), the other cases have never been studied before, except when the input graph is a cycle, in an abundant literature in topology and more recently by Despré and Lazarus [SoCG 2017, J. ACM 2019]. Our algorithm runs in O(m + poly(g+b) n log n) time, where g >= 0 and b >= 0 are the genus and the number of boundary components of the input orientable surface S, and n is the size of the input graph drawing, lying on some fixed graph of size m cellularly embedded on S. We use various techniques from two-dimensional computational topology and from the theory of hyperbolic surfaces. Most notably, we introduce reducing triangulations, a novel discrete analog of hyperbolic surfaces in the spirit of systems of quads by Lazarus and Rivaud [FOCS 2012] and Erickson and Whittlesey [SODA 2013], which have the additional benefit that reduced paths are unique and stable upon reversal; they are likely of independent interest. Tailored data structures are needed to achieve certain homotopy tests efficiently on these triangulations. As a key subroutine, we rely on an algorithm to test the weak simplicity of a graph drawn on a surface by Akitaya, Fulek, and Tóth [SODA 2018, TALG 2019].

This study focuses on online evacuation management. We design a framework to solve dynamic population evacuation (DPE) problems by creating an initial evacuation plan and employing inter-vehicle communication under a cloud computing architecture. For creating an initial plan, we formulate and solve dynamically (i) the shelter allocation problem (SAP) to choose a shelter node representing safety, and (ii) dynamic traffic assignment (DTA) to choose the best path leading towards the chosen destinations. The DPE process then begins with the planning phase to design a plan for the evacuation operation. Afterward, a vehicular ad hoc network (VANET) is deployed according to vehicular cloud computing (VCC) to make it possible for evacuees to share information and have online guidance from the server. We use vehicular communication to revise vehicle decisions initially taken by the plan, considering the dynamic progression of the catastrophe risk and congestion levels. To approve our new framework, we apply it to a real test case of Luxembourg city. We measure the clearance time and the mean evacuation time of the proposed solution and compare them with the results of other planning methods in the literature. Results show that online solving of DPE can minimize mean evacuation time and network clearance time by more than 10% compared to other models with only planning optimization. In addition, we analyze the performance of the proposed framework by changing the penetration rate of connected vehicles, and we observe that the increase in penetration rate leads to a decrease in network clearance time.

Large-scale pre-trained Vision & Language (VL) models have shown remarkable performance in many applications, enabling replacing a fixed set of supported classes with zero-shot open vocabulary reasoning over (almost arbitrary) natural language prompts. However, recent works have uncovered a fundamental weakness of these models. For example, their difficulty to understand Visual Language Concepts (VLC) that go 'beyond nouns' such as the meaning of non-object words (e.g., attributes, actions, relations, states, etc.), or difficulty in performing compositional reasoning such as understanding the significance of the order of the words in a sentence. In this work, we investigate to which extent purely synthetic data could be leveraged to teach these models to overcome such shortcomings without compromising their zero-shot capabilities. We contribute Synthetic Visual Concepts (SyViC) - a million-scale synthetic dataset and data generation codebase allowing to generate additional suitable data to improve VLC understanding and compositional reasoning of VL models. Additionally, we propose a general VL finetuning strategy for effectively leveraging SyViC towards achieving these improvements. Our extensive experiments and ablations on VL-Checklist, Winoground, and ARO benchmarks demonstrate that it is possible to adapt strong pre-trained VL models with synthetic data significantly enhancing their VLC understanding (e.g. by 9.9% on ARO and 4.3% on VL-Checklist) with under 1% drop in their zero-shot accuracy.

Audio Description (AD) is the task of generating descriptions of visual content, at suitable time intervals, for the benefit of visually impaired audiences. For movies, this presents notable challenges -- AD must occur only during existing pauses in dialogue, should refer to characters by name, and ought to aid understanding of the storyline as a whole. To this end, we develop a new model for automatically generating movie AD, given CLIP visual features of the frames, the cast list, and the temporal locations of the speech; addressing all three of the 'who', 'when', and 'what' questions: (i) who -- we introduce a character bank consisting of the character's name, the actor that played the part, and a CLIP feature of their face, for the principal cast of each movie, and demonstrate how this can be used to improve naming in the generated AD; (ii) when -- we investigate several models for determining whether an AD should be generated for a time interval or not, based on the visual content of the interval and its neighbours; and (iii) what -- we implement a new vision-language model for this task, that can ingest the proposals from the character bank, whilst conditioning on the visual features using cross-attention, and demonstrate how this improves over previous architectures for AD text generation in an apples-to-apples comparison.

The objective of this paper is an automatic Audio Description (AD) model that ingests movies and outputs AD in text form. Generating high-quality movie AD is challenging due to the dependency of the descriptions on context, and the limited amount of training data available. In this work, we leverage the power of pretrained foundation models, such as GPT and CLIP, and only train a mapping network that bridges the two models for visually-conditioned text generation. In order to obtain high-quality AD, we make the following four contributions: (i) we incorporate context from the movie clip, AD from previous clips, as well as the subtitles; (ii) we address the lack of training data by pretraining on large-scale datasets, where visual or contextual information is unavailable, e.g. text-only AD without movies or visual captioning datasets without context; (iii) we improve on the currently available AD datasets, by removing label noise in the MAD dataset, and adding character naming information; and (iv) we obtain strong results on the movie AD task compared with previous methods.

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Abstract Although automatic sequences are very simple algorithmically, some of them have pseudo-random properties. In particular, some automatic sequences such as the Golay–Shapiro sequence are known to be 2-uncorrelated, meaning that they have the same correlations of order 2 as a uniform random sequence. However, the existence of ℓ -uncorrelated automatic sequences (for ℓ ⩾ 3) was left as an open question in a recent paper of Marcovici, Stoll and Tahay. We exhibit binary block-additive sequences that are 3-uncorrelated and, with the help of analytical results supplemented by an exhaustive search, we present a complete picture of the correlation properties of binary block-additive sequences of rank r ⩽ 5, and ternary sequences of rank r ⩽ 3.

We study the IS-algorithm, a well-known linear-time algorithm for computing the suffix array of a word. This algorithm relies on transforming the input word w into another word, called the reduced word of w, that will be at least twice shorter; then, the algorithm recursively computes the suffix array of the reduced word. In this article, we study the reduction ratio of the IS-algorithm, i.e., the ratio between the lengths of the input word and the word obtained after reducing k times the input word. We investigate both worst cases, in which we find precise results, and random cases, where we prove some strong convergence phenomena. Finally, we prove that, if the input word is a randomly chosen word of length n, we should not expect much more than log(log(n)) recursive function calls.

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Recently, deep neural networks (DNNs) have been utilized in real-time systems such as autonomous vehicles, where meeting temporal constraints is essential. However, executing such systems on CPU-GPU architectures can make scheduling analysis challenging due to the added delays caused by computing and memory contention. In addition, classic task models are not directly able to model accurately such systems. In this article, we propose a new task model called DNN Task Model (DTM). This model considers both DNN properties and GPU architecture at the same time. It allows us to distinguish between CPU and GPU tasks, provides information about the DNN application and give more accurate execution time analysis through consideration of data quality. We compute DTM from a source CUDA file and a set of real-time specifications of the system. The proposed model is extensible enough to be adopted to various DNN type applications allowing designer to compare candidate software and GPU architectures. Furthermore, we propose a graph optimization inspired by Tensor-RT.

When faced with data corrupted by both noise and outliers robust estimation algorithms like RanSaC are used, especially in the field of Multi-View Stereo (MVS) or Structure-from-Motion (SfM). To find the best model fitting the data, from numerous minimal samples it evaluates models and rates them according to their number of inliers. The classification as inlier depends on a user-set threshold that should be tailored to the noise level of the data. This requires the knowledge of this level, which is rarely available. The few existing adaptive threshold algorithms solve this problem by estimating the value of the threshold while computing the best model. However, it is hard to obtain groundtruth for MVS and SfM tasks and usually test datasets are based on the output on some state of the art algorithm, which prevents the objective evaluation of new algorithms. We propose a new method to generate artificial datasets based on true data to get realistic and measurable results. We use this method to benchmark different automatic RanSaC algorithms and find out how they compare to each other and identify each algorithm's strengths and weaknesses. This study reveals uses cases for each method and the possible tradeoffs between performance and execution time.

Radar is an indispensable part of the Internet of Things (IoT). Specific emitter identification is essential to identify the legitimate radars and, more importantly, to reject the malicious radars. Conventional methods rely on pulse parameters that are not capable to identify the specific emitter as two radars may have the same configuration or a malicious radar can perform spoofing attacks. Radio frequency fingerprint (RFF) is the unique and intrinsic hardware characteristic of devices resulted from hardware imperfection, which can be used as the device identity. This paper proposes a robust and reliable radar identification scheme based on the RFF, taking linear frequency modulation (LFM) radar as a case study. This scheme first classifies the operation mode of the pulses, then eliminates the noise effect, and finally identifies the radar emitters based on the transient and modulation-based RFF features. Experimental results verify the effectiveness of our radar identification scheme among three real LFM radars (same model) operating at four modes, each mode with 2,000 pulses from each radar. The identification rates of the four modes are all higher than 90% when the signal-tonoise ratio (SNR) is about 5 dB. In addition, mode 3 achieves almost 100% identification accuracy even when the SNR is as low as-10 dB.

Computer tools allow to ease the daily life of everyone, especially for people with disabilities. The optimal choice of pointing interfaces or types of settings can be difficult to achieve. Although there exist a few tests to compare and evaluate the performance of computer access technology (CAT), most of them only provide results as qualitative terms. Besides, the current choice is based mainly on clinical observations or non-standardized tests. To objectify the recommendations in CAT, support funding for people with disabilities and measure the functional repercussions of a therapeutic action, it is necessary to carry out comparative tests with measurable criteria. This paper presents the development of a personalized, free, and dedicated evaluation platform of pointing interfaces and aids. The quantitative evaluation process is described in detail, including the configuration of different exercises with settable parameters that permits to build a customized evaluation process with increased difficulties, the definition of performance indicators and the statistical analysis methods for quantified comparative tests. Finally, we present the assessment results of four people with different disabilities using multiple pointing interfaces, which verify the effectivity of this evaluation platform with the help of occupational therapists.

Particle-based deep generative models, such as gradient flows and score-based diffusion models, have recently gained traction thanks to their striking performance. Their principle of displacing particle distributions using differential equations is conventionally seen as opposed to the previously widespread generative adversarial networks (GANs), which involve training a pushforward generator network. In this paper we challenge this interpretation, and propose a novel framework that unifies particle and adversarial generative models by framing generator training as a generalization of particle models. This suggests that a generator is an optional addition to any such generative model. Consequently, integrating a generator into a score-based diffusion model and training a GAN without a generator naturally emerge from our framework. We empirically test the viability of these original models as proofs of concepts of potential applications of our framework.

Cet article est consacré à l'estimation de la dimension minimale P des représentations d'état d'une série temporelle multivariable (yn) n∈Z de dimension M définie comme une version bruitée (le bruit est gaussien et blanc temporellement) d'un signal utile (un) n∈Z dont la densité spectrale est rationnelle et de petit rang. Cette étude est menée dans le régime des grandes dimensions dans lequel le nombre d'échantillons disponibles N et la dimension des observations M sont grands et du même ordre de grandeur. En utilisant des techniques de grandes matrices aléatoires, il est établi que l'analyse des plus grands coefficients de corrélation canonique estimés entre le passé et le futur de y permet d'évaluer de faccon consistante P si des conditions liées au rapport signal sur bruit et aux coefficients de corrélation canonique entre le passé et le futur du signal u sont vérifiées

Dans cet article, nous proposons un nouveau test permettant de vérifier l'indépendance mutuelle d'un grand nombre de signaux dans le cas où le nombre d'observations disponible est limité. Le test utilise des statistiques linéaires des valeurs propres de la matrice de cohérence spectrale estimée, évaluées sur une grille de fréquence bien choisie. Nous montrons que sous l'hypothèse d'indépendance, la statistique de test bien recentrée et normalisée converge en loi vers une gaussienne standard. Cela permet d'évaluer l'erreur de première espèce asymptotique du test.

We investigate the asymptotic distribution of the maximum of a frequency smoothed estimate of the spectral coherence of a M-variate complex Gaussian time series with mutually independent components when the dimension M and the number of samples N both converge to infinity. If B denotes the smoothing span of the underlying smoothed periodogram estimator, a type I extreme value limiting distribution is obtained under the rate assumptions M N → 0 and M B → c ∈ (0, +∞). This result is then exploited to build a statistic with controlled asymptotic level for testing independence between the M components of the observed time series. Numerical simulations support our results.

In this article, we propose an incremental method for computing seeded watershed cuts for interactive image segmentation. We propose an algorithm based on the hierarchical image representation called the binary partition tree to compute a seeded watershed cut. We show that this algorithm fits perfectly in an interactive segmentation process by handling user interactions, seed addition or removal, in time linear with respect to the number of affected pixels. Run time comparisons with several state-of-the-art interactive and noninteractive watershed methods show that the proposed method can handle user interactions much faster than previous methods, thus improving the user experience on large images.

Aging is a key problem in our daily life which demands more technology such as the terrain classification recognition for the detailed path planning. In this article, a six-axis accelerometer was placed on the base of a walking stick to capture walking gait vibration information. The signal features in the collected information were used to reflect the terrain. We used a matching tracking method to decompose the signal data into linear combinations of Gabor atoms and a joint time-frequency analysis method to perform analysis on the topographic features in a three-dimensional space. Three types of terrains were classified from space-time data. Results show that the proposed algorithm could achieve an average accuracy rate of 88.6%, which is 4% higher than conventional methods.

The EIDA project explores the historical use of astronomical diagrams across Asia, Africa, and Europe. We aim to develop automatic image analysis tools to analyze and edit these diagrams without human annotation, gaining a refined understanding of their role in shaping and transmitting astronomy. In this paper, we present a baseline method to detects lines and circles in historical diagrams, based on text removal, edge detection and RANSAC. We compare this strong baseline to a deep learning approach based on LETR. This work contributes to historical diagram vectorization, enabling novel methods of comparison and clustering, and offering fresh insights into the vast corpus of astronomical diagrams.

Class-wise characteristics of training examples affect the performance of deep classifiers. A well-studied example is when the number of training examples of classes follows a long-tailed distribution, a situation that is likely to yield suboptimal performance for under-represented classes. This class imbalance problem is conventionally addressed by approaches relying on the class-wise cardinality of training examples, such as data resampling. In this paper, we demonstrate that considering solely the cardinality of classes does not cover all issues causing class imbalance. To measure class imbalance, we propose CLASS UNCERTAINTY as the average predictive uncertainty of the training examples, and we show that this novel measure captures the differences across classes better than cardinality. We also curate SVCI-20 as a novel dataset in which the classes have equal number of training examples but they differ in terms of their hardness; thereby causing a type of class imbalance which cannot be addressed by the approaches relying on cardinality. We incorporate our CLASS UNCERTAINTY measure into a diverse set of ten class imbalance mitigation methods to demonstrate its effectiveness on long-tailed datasets as well as on our SVCI-20. Code and datasets will be made available.

In this paper, we describe a graph-based algorithm that uses the features obtained by a self-supervised transformer to detect and segment salient objects in images and videos. With this approach, the image patches that compose an image or video are organised into a fully connected graph, where the edge between each pair of patches is labeled with a similarity score between patches using features learned by the transformer. Detection and segmentation of salient objects is then formulated as a graph-cut problem and solved using the classical Normalized Cut algorithm. Despite the simplicity of this approach, it achieves state-of-the-art results on several common image and video detection and segmentation tasks. For unsupervised object discovery, this approach outperforms the competing approaches by a margin of 6.1%, 5.7%, and 2.6%, respectively, when tested with the VOC07, VOC12, and COCO20K datasets. For the unsupervised saliency detection task in images, this method improves the score for Intersection over Union (IoU) by 4.4%, 5.6% and 5.2%. When tested with the ECSSD, DUTS, and DUT-OMRON datasets, respectively, compared to current state-of-the-art techniques. This method also achieves competitive results for unsupervised video object segmentation tasks with the DAVIS, SegTV2, and FBMS datasets.

The VHS project (computer Vision and Historical analysis of Scientific illustration circulation) proposes a new approach to the historical study of the circulation of scientific knowledge based on new methods of illustration analysis. Our contributions in this paper are twofold. First, we present a semi-automatic interactive pipeline for scientific illustration extraction that allows and incorporates expert feedback from historians. Second, we introduce a new dataset of scientific illustrations from the Middle Ages to the modern era consisting of 8k illustrations validated by historians and a total number of 235k illustrations obtained from 405k corpora pages. We further discuss our current research for identifying a series of related illustrations from this data.

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An automaton is synchronizing when there is a word that brings every state into one and the same state. Such a word is called a synchronizing word, and Černý conjectured in 1964 that if a n-state deterministic automaton is synchronizing, then it has a synchronizing word of length at most (n − 1)². The best bound known so far is cubic in n and was obtained by Szykuła in 2017. In this article, we study the synchronization properties of random deterministic automata, for the uniform distribution. Berlinkov recently proved that they are synchronizing with high probability. Our contribution is to study the typical length of the smallest synchronizing word, when such a word exists: we establish that with high probability, such an automaton with n states admits a synchronizing word of length O(n log^3 n). As a byproduct, we get that for most automata, the Černý conjecture holds.

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Neural implicit surfaces have become an important technique for multi-view 3D reconstruction but their accuracy remains limited. In this paper, we argue that this comes from the difficulty to learn and render high frequency textures with neural networks. We thus propose to add to the standard neural rendering optimization a direct photo-consistency term across the different views. Intuitively, we optimize the implicit geometry so that it warps views on each other in a consistent way. We demonstrate that two elements are key to the success of such an approach: (i) warping entire patches, using the predicted occupancy and normals of the 3D points along each ray, and measuring their similarity with a robust structural similarity (SSIM); (ii) handling visibility and occlusion in such a way that incorrect warps are not given too much importance while encouraging a reconstruction as complete as possible. We evaluate our approach, dubbed NeuralWarp, on the standard DTU and EPFL benchmarks and show it outperforms state of the art unsupervised implicit surfaces reconstructions by over 20% on both datasets. Our code is available at https://github.com/fdarmon/NeuralWarp

Deep multi-view stereo (MVS) methods have been developed and extensively compared on simple datasets, where they now outperform classical approaches. In this paper, we ask whether the conclusions reached in controlled scenarios are still valid when working with Internet photo collections. We propose a methodology for evaluation and explore the influence of three aspects of deep MVS methods: network architecture, training data, and supervision. We make several key observations, which we extensively validate quantitatively and qualitatively, both for depth prediction and complete 3D reconstructions. First, complex unsupervised approaches cannot train on data in the wild. Our new approach makes it possible with three key elements: upsampling the output, softmin based aggregation and a single reconstruction loss. Second, supervised deep depthmap-based MVS methods are state-of-the art for reconstruction of few internet images. Finally, our evaluation provides very different results than usual ones. This shows that evaluation in uncontrolled scenarios is important for new architectures.

We tackle the problem of finding accurate and robust keypoint correspondences between images. We propose a learning-based approach to guide local feature matches via a learned approximate image matching. Our approach can boost the results of SIFT to a level similar to state-of-theart deep descriptors, such as Superpoint, ContextDesc, or D2-Net and can improve performance for these descriptors. We introduce and study different levels of supervision to learn coarse correspondences. In particular, we show that weak supervision from epipolar geometry leads to performances higher than the stronger but more biased point level supervision and is a clear improvement over weak image level supervision. We demonstrate the benefits of our approach in a variety of conditions by evaluating our guided keypoint correspondences for localization of internet images on the YFCC100M dataset and indoor images on the SUN3D dataset, for robust localization on the Aachen daynight benchmark and for 3D reconstruction in challenging conditions using the LTLL historical image data.

Most deep pose estimation methods need to be trained for specific object instances or categories. In this work we propose a completely generic deep pose estimation approach, which does not require the network to have been trained on relevant categories, nor objects in a category to have a canonical pose. We believe this is a crucial step to design robotic systems that can interact with new objects in the wild not belonging to a predefined category. Our main insight is to dynamically condition pose estimation with a representation of the 3D shape of the target object. More precisely, we train a Convolutional Neural Network that takes as input both a test image and a 3D model, and outputs the relative 3D pose of the object in the input image with respect to the 3D model. We demonstrate that our method boosts performances for supervised category pose estimation on standard benchmarks, namely Pascal3D+, ObjectNet3D and Pix3D, on which we provide results superior to the state of the art. More importantly, we show that our network trained on everyday man-made objects from ShapeNet generalizes without any additional training to completely new types of 3D objects by providing results on the LINEMOD dataset as well as on natural entities such as animals from ImageNet.

Le japonais et le français partagent un mécanisme pour exprimer subjectivement le haut degré d’une propriété. Il prend la forme de constructions syntaxiques particulières, ayant leurs propres forme et sens, avec une valeur pragmatique bien délimitée. En japonais, donnani forme une construction indépendante et une construction dépendante, en corrélation avec la fin de phrase kotoka. En français, à quel point se construit presque exclusivement en subordonnée, dépendant de prédicats qui excluent l’interprétation de questionnement. Malgré leur forme interrogative, ils ne sont pas employés pour poser une question dans un dialogue mais pour former l’argument de la prédication d’indicibilité ou d’incompréhension, le tout constituant une exclamation.

Le marqueur "C'est pour moi que tu dis ça ?" (CPM) est un signe d'inférence contextuelle qui dénonce et conteste une allusion négative à l'encontre du locuteur du marqueur (L 2), qu'il croit entendre comme une voix masquée sous un énoncé d'un autre locuteur (L 1). L'implicite, volontaire ou involontaire et insaisissable linguistiquement, se dévoile par l'énonciation même de CPM, qui assigne à L 2 , allocutaire ou non de L 1 , le rôle de destinataire de l'implicite. CPM est dialogal : il présuppose l'énonciation préalable de L 1 et l'énoncé de L 1 présente la caractéristique fondamentale d'être interprété comme une allusion par une figure rhétorique d'association. L 2 ne se contente pas de dévoiler une allusion mais la conteste simultanément : CPM est un argument co-orienté avec un énoncé assertant le contraire de ce qui est inféré. L 1 est invité à nier l'intention allusive.

Version Control Systems, used by developers to keep track of the evolution of their code, model repositories as Merkle graphs of revisions. In order to synchronize efficiently between different instances of a repository, they need to determine the common knowledge that they share. This process is called discovery. In this paper, we provide theoretical definitions for the problem of discovery and establish some universal upper and lower bounds on its communication complexity. We also present and analyze some algorithms that are used in extant VCSs, such as Mercurial and Git.

L'un des principaux objectifs de la surveillance de santé structurale (SHM) est de détecter, et éventuellement localiser, quantifier ou prédire les dommages sur les structures. Sans connaissances détaillées du comportement mécanique structurel, l'analyse des données est une tâche complexe, et la surveillance opérationnelle est souvent limitée à l'utilisation de seuils plus ou moins arbitraires. Les approches data-driven qui reposent sur une analyse statistique des données, ont suscité un intérêt croissant ces deux dernières décennies. Cet article propose une approche basée sur plusieurs modèles automatisés construits par apprentissage automatique, pour la détection et la localisation des anomalies dans les données de surveillance d'un grand pont en béton. Pour chaque capteur, plusieurs modèles de régression sont générés à l’aide de réseaux de neurones récurrents en utilisant les données d'autres capteurs déployés sur la structure. Les anomalies sont ensuite identifiées dans le jeu de données en fonction des résidus entre les sorties des modèles et les données mesurées in situ. Pour un capteur donné, les résidus de tous les modèles sont ensuite compilés pour produire un indicateur d'anomalie.

Monte Carlo Search algorithms can give excellent results for some combinatorial optimization problems and for some games. They can be parallelized efficiently on high-end CPU servers. Nested Monte Carlo Search is an algorithm that parallelizes well. We take advantage of this property to obtain large speedups running it on low cost GPUs. The combinatorial optimization problem we use for the experiments is the Snake-in-the-Box. It is a graph theory problem for which Nested Monte Carlo Search previously improved lower bounds. It has applications in electrical engineering, coding theory, and computer network topologies. Using a low cost GPU, we obtain speedups as high as 420 compared to a single CPU.