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Background Surging acceptance of adaptive cruise control (ACC) across the globe is further escalating concerns over its energy impact. Two questions have directed much of this project: how to distinguish ACC driving behaviour from that of the human driver and how to identify the ACC energy impact. As opposed to simulations or test-track experiments as described in previous studies, this work is unique because it was performed in real-world car-following scenarios with a variety of vehicle specifications, propulsion systems, drivers, and road and traffic conditions. Methods Tractive energy consumption serves as the energy impact indicator, ruling out the effect of the propulsion system. To further isolate the driving behaviour as the only possible contributor to tractive energy differences, two techniques are offered to normalize heterogeneous vehicle specifications and road and traffic conditions. Finally, ACC driving behaviour is compared with that of the human driver from transient and statistical perspectives. Its impact on tractive energy consumption is then evaluated from individual and platoon perspectives. Results Our data suggest that unlike human drivers, ACC followers lead to string instability. Their inability to absorb the speed overshoots may partly be explained by their high responsiveness from a control theory perspective. Statistical results might imply the followers in the automated or mixed traffic flow generally perform worse in reproducing the driving style of the preceding vehicle. On the individual level, ACC followers have tractive energy consumption 2.7 – 20.5 % higher than those of human counterparts. On the platoon level, the tractive energy values of ACC followers tend to consecutively increase (11.2 – 17.3 %). Conclusions In general, therefore, ACC impacts negatively on tractive energy efficiency. This research provides a feasible path for evaluating the energy impact of ACC in real-world applications. Moreover, the findings have significant implications for ACC safety design when handling the stability-responsiveness trade-off.

CETRA 2020, 6th International Conference on Road and Rail Infrastructure - Online, Pula, CROATIE, 20-/05/2021 - 21/05/2021; 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.

Multiple factors can influence the public transport level of service. All take root in the network structure and the operating regime, i.e. how the bus lines are arranged atop the street network and how the service frequency is adjusted to meet urban mobility patterns. This is known as the bus network design problem and has been the subject of several studies. The problem is so challenging that most studies until now resort to strong assumptions such as a static description of the peak hour demand, homogeneous user behavior, and equal trip lengths. Potential effects of different types of user behavior and trip lengths patterns on the user and/or operator cost have not been investigated whatsoever. Moreover, none of the existing studies have considered the effects of bus network structure on private car users, the level of interactions between the modes, and the passenger mode choice that depends on traffic conditions. This paper aims to close this gap and provide a general framework considering multiple trip length patterns, two types of user behavior, and the effects that the bus network structure might have on the traffic performance and passenger mode choice. For modeling different trip length patterns, we use the trip length distribution as an intermediate level of abstraction. To capture complex modal interactions and quantify the operating speeds, we apply the recently proposed three-dimensional macroscopic fundamental diagram. We use the operating speed for each mode to determine the mode choice at the trip length level. This way, we are able to solve the optimal bus network design problem under the free-flow/saturated traffic conditions in an analytical way, while considering more realistic settings including a dynamic description of the peak hour demand, mixed traffic, and different mode choice decisions depending on trip lengths and walking preferences. Numerical analysis reveals that all the tested factors, including demand intensity, user behavior, and trip length patterns, have significant effects on the operator and user cost function. Results show that the probability of choosing any given mode follows certain distribution that varies across the trip length patterns, indicating the importance of modeling the mode choice at the trip length level. Furthermore, the results indicate that users can benefit if they are willing to adjust the number of transfers to minimize the walking distance at the origin and the destination. Moreover, we show that the optimal bus network design determined for the uniform trip pattern underestimates the number of required buses, which leads to passenger congestion at stops during the peak period. This, however, does not happen when we take into account the actual trip length distribution for the bus network design. A comparison with a simplified approach that considers the bus system only, reveals the value of accounting for the complex bi-modal interactions, especially for higher demand levels. Finally, we show that by allowing the design parameters to vary across cardinal directions we provide more flexibility for the bus system to serve the passenger demand while reducing the operator cost compared to the existing approaches. ISSN:0191-2615 ISSN:1879-2367

Over the past few decades, the digitalization of services and infrastructures has led to the emergence of a broad set of new information sources to characterize human mobility. These sources usually offer valuable significant population penetration rates but may also suffer from important temporal sparsity. Data generated by user activity, such as social networks or mobile phone data, especially fit this description. Although this temporal sparsity might prevent estimating individual travel speeds, we state that such low-frequency positioning data enable estimating the average urban traffic speed dynamics when considering an adequate network partitioning. In this sense, this article proposes a new method, based on the division of the urban area of a given city into regions and on the analysis of a limited set of basic characteristics of individual vehicle trips, such as the regional path. Our solution first involves estimating robust travel times from travelers sharing similar trip features and then jointly analyzing these travel times to deduce the underlying regional traffic speeds, using regression analysis. We apply this methodology on a set of trips derived from a large GPS dataset of vehicle tracks covering the city of Lyon. These data are purposely downsampled to reduce the sampling rate and reproduce bias and temporal features that are proper to sparser but larger-scale, mobility data sources dependent on user’s communication activities. Controlling the data downsampling process allows us to evaluate the impacts of the progressive information loss on the speed estimation, while the raw GPS data provide the ground truth speed reference against which to compare our results. Provided that the amount of observed individual trips is sufficient, the analysis returns satisfying speed estimation results, both at low and high downsampling levels. Thus, we successfully demonstrate that it is possible to estimate zonal traffic speeds from degraded trip data without evaluating individual travel speeds.

This work investigates network-related trajectory features to unravel trips that contribute most to system under-performance. When such trips are identified, feature analysis also permits determining the best alternatives in terms of routes to bring the system to its optimum. First, we define a combination of network-related trajectory features that helps us unravel the critical trips which contribute the most to the network under-performance, based on the literature review and a factor selection process. Second, based on supervised learning methods, we propose a two-step data-driven methodological framework to reroute a part of the users and make the system close to its optimum. The learning models are trained with trajectory features to identify which users should be selected, and which alternative routes should be assigned, thanks to the data and features obtained from two reference dynamic traffic assignment (DTA) simulations, under User-Equilibrium (UE) and System-Optimum (SO). We only focus on trajectory features that are accessible in real time, such as network features and regular travel time information, so that the methods proposed can be implemented without requiring cumbersome network monitoring and prediction. Finally, we evaluate the efficiency of the methods proposed through microscopic DTA simulations. The results show that by targeting 20% of the users according to our selection model and moving them onto paths predicted as optimal alternative paths based on our rerouting model, the total travel time (TTT) of the system is reduced by 5.9% in comparison to a UE DTA simulation. This represents 62.5% of the potential TTT reduction from UE to SO, when all the users choose their path under the SO condition.

COMPRAIL 2020 : 17th International Conference on Railway Engineering Design & Operation, Berlin, ALLEMAGNE, 01-/07/2020 - 03/09/2020; In this paper we propose an experimental study aimed to assess a new paradigm for railway traffic management. In current practice and academic state of the art, train priority decisions in case of perturbation are made centrally. In this work, train traffic is modelled as a multi-agent system in which trains are decision makers. We implement a microscopic simulator for assessing the viability of this decentralized traffic management and for comparing it with the centralized one. Our results show that it is indeed possible to let trains decide their own priority and it is possible to achieve results which are comparable to simple centralized approaches in terms of passenger travel time in the mass-transit area of Paris, in France.

Multi-modal interactions at the network-level remain unexplored due to the lack of high-resolution data for all transportation modes involved. The current work investigates the effect of multi-modal interactions at space-mean network speed for each mode using the dataset from pNEUMA experiment that was carried out in a congested city centre network of Athens, Greece. Explanatory variables considered are the accumulation and the stopped fraction of vehicles of each mode. Firstly, a multi-modal mean speed MFD is considered by assuming that the mean speed of each mode can be expressed in terms of accumulations of all modes. The quality of multi-modal MFD fits is compared to the uni-modal ones, where the mean speed of a given mode is assumed to be a function of the accumulation of that mode only. Secondly, the classical two-fluid model is extended to multi-modal networks. An analysis on the ergodicity assumption in the context of stopped fraction is also presented. This work also introduces a network-level dynamic model that uses the stopped fraction of vehicles. This so-called extended trip-based model simulates the stop-and-go pattern of the vehicles thereby reproducing the evolution of network congestion. This work is the first to explore in this direction. The results from the classical trip-based and the extended trip-based models are compared and validated with the empirical data.

Although emission models have been designed using vehicle data over driving cycles of a few minutes, they are often applied at large scale to estimate total emission (inventories). In between, there is a range of scales in use in traffic and environmental studies (road sections, sub-areas, etc.). Coupling a traffic microsimulation with COPERT emission factors at different scales reveals scaling biases. We compare network fuel consumption (FC) and nitrogen oxide (NOx) emissions resulting from emission calculations based on different spatial decompositions. The results show that for an area of Paris covering 3 km2, the differences due to the aggregation scale for emissions range from 5 to 17% depending on the pollutant, spatial partitioning and traffic conditions. These discrepancies can be reduced using a distance-weighted mean speed, which is not a scale-consistent definition of mean travel speed. They can almost be cancelled by using a correction term derived analytically in this paper, thus consistency can be guaranteed between emissions assessed at different scales. Finally, a case study shows that it is possible to evaluate FC and NOx emissions on a large-scale network from a sample of traffic data (probes), and obtain the corrective term to be applied to remove scaling bias. The most critical step is the accurate estimation of the total travel distance. The gaps were successfully reduced to a maximum of 8% in congestion for a penetration rate of about 20%.

RailNorrköping 2019, 8th International Conference on Railway Operations Modelling and Analysis (ICROMA), Norrköping, SUEDE, 17-/06/2019 - 20/06/2019; In railway traffic management problems, a frequent approximation is the one of fixed-speed, i.e. the trains either run at their cruise speed or are stopped immediately without considering the acceleration and deceleration phases due to arising conflicts on the infrastructure. We assess the validity of the fixed-speed approximation for train speed dynamics in the real time Railway Traffic Management Problem. This is done through a statistical analysis on a number of perturbed scenarios on different railway infrastructures, for different objective functions commonly used in the literature. For each scenario, we analyze the ranking of the generated solutions both in the fixed-speed approximation, obtained by solving the optimization model, and with the variable-speed dynamics, obtained through micro simulation with the OpenTrack software. Our results indicate that some objective functions can be considered reliable when used in conjunction with the fixed-speed approximation, while others require more detailed studies. We also propose a modi?ed fixed-speed approximation to better reflect the behaviour of trains speed dynamics and study its efficiency.

Modelling approaches for simulating air and stormwater pollution due to on-road vehicles are reviewed and discussed. Models for traffic, emissions, atmospheric dispersion, and stormwater contamination are studied with particular emphasis on their couplings to create a modelling chain. The models must be carefully selected according to the requirements and level of detail of the integrated modelling chain. Although a fair amount of research has been conducted to link air pollution and road traffic, many questions related to spatio-temporal scales, domains of validity, consistency among models, uncertainties of model simulation results, and interfaces between models remain open. The aim of this work is to review the current status of the relationships between traffic, emissions, air quality, and water quality models, to recommend modelling approaches and to propose some directions for improving the state of the science. The difficulties and challenges associated with model coupling are illustrated with specific examples. We present a state of the art of traffic, emissions, atmospheric dispersion and stormwater models.We review modelling approaches for simulating air and water pollution with particular emphasis on their couplings.The difficulties and challenges associated with model coupling are discussed with three specific examples.We propose two modelling chains to simulate the environmental impacts of traffic for both average-based and dynamic models.

ITST 2017 - 15th International Conference on ITS Telecommunications, Warsaw, POLOGNE, 29-/05/2017 - 31/05/2017; Vehicular communications can be achieved through the infrastructure (Vehicle-to-infrastructure network, V2I), as well as directly through vehicle-to-vehicle communication (V2V) via ad hoc networks. In V2V communications, the routing protocols are designed in order to optimize the dissemination of messages. This paper presents an evaluation of routing protocols such as the Optimized Link State Routing (OLSR), Ad hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR), and Geographic Routing Protocol (GRP), while considering both vehicular safety application requirements and mobility models based on real-world traces of vehicular traffic. The results show that, though proactive routing protocols perform better in this context, the four routing protocols fail to fulfill the safety application requirements on the delay metric even for a reasonable number of vehicles.

VEHICULAR 2017 - The Sixth International Conference on Advances in Vehicular Systems, Technologies and Applications, Nice, FRANCE, 23-/07/2017 - 27/07/2017; Routing protocols for vehicular ad hoc networks resort to clustering to optimize network performance. In existing proposals, cluster-heads are chosen based on various metrics such as the number of its direct neighbors, the quality of the links, etc. Other clustering techniques consider the geographic environment of the roads, and they choose one cluster-head for each space subdivision. The clustering scheme proposed in this work combines the information on road configuration, vehicle mobility and link quality in order to build a structure similar to vehicular network infrastructure, while relying only on the vehicles. The evaluations show that this scheme allows creating and maintaining during a significant time a small number of stable connected groups, in most cases, just one in each traffic direction. This clustering scheme can be integrated into any reactive, proactive, or geographic ad hoc routing protocol in order to optimize the flooding and simplify route maintenance. And it allows the routing protocol to operate without any global location information service.

Using a fixed-base driving simulator we compared the effects of the size and type of traffic vehicles (i.e., normal-sized or double-sized cars or motorcycles) approaching an intersection in two different tasks. In the perceptual judgment task, passively moving participants estimated when a traffic vehicle would reach the intersection for actual arrival times (ATs) of 1, 2, or 3 s. In line with earlier findings, ATs were generally underestimated, the more so the longer the actual AT. Results revealed that vehicle size affected judgments in particular for the larger actual ATs (2 and 3 s), with double-sized vehicles then being judged as arriving earlier than normal-sized vehicles. Vehicle type, on the other hand, affected judgments at the smaller actual ATs (1 and 2 s), with cars then being judged as arriving earlier than motorcycles. In the behavioral task participants actively drove the simulator to cross the intersection by passing through a gap in a train of traffic. Analyses of the speed variations observed during the active intersection-crossing task revealed that the size and type of vehicles in the traffic train did not affect driving behavior in the same way as in the AT judgment task. First, effects were considerably smaller, affecting driving behavior only marginally. Second, effects were opposite to expectations based on AT judgments: driver approach speeds were larger (rather than smaller) when confronted with double-sized vehicles as compared to their normal-sized counterparts and when confronted with cars as compared to motorcycles. Finally, the temporality of the effects was different on the two tasks: vehicle size affected driver approach speed in the final stages of approach rather than early on, while vehicle type affected driver approach speed early on rather than later. Overall, we conclude that the active control of approach to the intersection is not based on successive judgments of traffic vehicle arrival times. These results thereby question the general belief that arrival time estimates are crucial for safe interaction with traffic.

L'objectif de ce travail consiste en la modélisation des flux de véhicules d'un grand et dense réseau de transport multimodal. Le travail s'organise en deux parties: un aspect théorique et un aspect développement. L'étude théorique met l'accent sur la façon dont un réseau multimodal peut être modélisé et comment sa performance en termes d'offre peut être optimisée. Pour ce faire' trois études principales sont réalisées: la prévision et la régulation des flux de trafic sur les grands réseaux de surface' la multimodalité véhiculaire dans les grands réseaux de surface prenant en compte les nouvelles formes de mobilité' et enfin l'impact de l'information sur le coût des itinéraires. La partie développement consiste en la conception d'un simulateur de flux de trafic pour réguler le trafic multimodal véhiculaire. Le simulateur développé devrait aider les opérateurs de transport et les collectivités territoriales dans leurs stratégies de gestion des flux de trafic The objective of this work consists on the modeling of traffic flow of a large multimodaltransportation network. The work is organized in two parts: a theoretical study part anda development part. The theoretical study emphasizes on how a multimodal network canbe model and how its performance in terms of supply can be optimized. To do so, threemain studies are discussed: the traffic flow prediction and regulation on large surface net-works, the vehicular multimodality in big surface networks taking into account new forms ofmobility, and finally the impact of the information on the cost of the itineraries. The devel-opment part consists on the conception of a traffic flow simulator to regulate the vehicularmultimodal traffic. The developed simulator should assist transport operators and territorialcommunities in their traffic flow management strategies

TRB 2017, Transportation research board annual meeting, Washington DC, ETATS-UNIS, 08-/01/2017 - 12/01/2017; The paper proposes a model-based framework for estimating traffic states from Eulerian (loop) and/or Lagrangian (probe) data. Lagrangian-Space formulation of the LWR model adopted as the underlying traffic model provides suitable properties for receiving both Eulerian and Lagrangian external information. Three independent methods are proposed to address Eulerian data, Lagrangian data and the combination of both, respectively. These methods are defined in a consistent framework so as to be implemented simultaneously. The proposed framework has been verified on the synthetic data derived from the same underlying traffic flow model. Strength and weakness of both data sources are discussed. Next, the proposed framework has been applied to a freeway corridor. The validity and performance have been tested using the data from a microscopic simulator.

hEART2016 Symposium, Delft , PAYS-BAS, 14-/09/2016 - 16/09/2016; Simulation using Macroscopic Fundamental Diagram (MFD) may be very sensitive to network heterogeneities, and the assumption of a constant rip length for travellers in a reservoir may lead to inaccurate results.

Among the four major skills identified by Tolmie for street crossing, namely 1) choose a safe place, 2) analyze the situation, 3) identify the time gaps, and 4) anticipate the behavior of others, the first three are related to the knowledge and the know-how, while the latter is directly related to life skills. Most virtual reality tools dedicated to street crossing only refer to the first three skills and systematically forget the last one. The proposal aims to identify barriers and proposes new research within an interdisciplinary framework, in order to enhance existing knowledge and develop new tools., Sur les 4 grands compétences identifiées par Tolmie pour la traversée de rue, à savoir 1)choisir un lieu sur, 2) analyser la situation, 3) identifier les créneaux temporels, et 4) anticiper les comportements d'autrui, les trois premières relèvent des savoirs et des savoir-faire, tandis que la dernière est directement liée aux savoir-être. La plupart des outils de simulation en réalité virtuelle développés de part le monde et dédiés à la traversée de rue ne font référence qu'aux trois premières compétences et oublient systématiquement la dernière. La proposition vise à identifier les obstacles et proposer des pistes de recherches qui s'inscrivent dans un cadre interdisciplinaire, afin de pouvoir enrichir les connaissances actuelles et développer de nouveaux outils.

FISICA 2016, 20 Conferencia Nacional de Fisica, Braga, PORTUGAL, 08-/09/2016 - 10/09/2016; We aim to develop a refined macroscopic simulation procedure, by tackling the calculation of path lengths and shortest path travel time; assignment/reassignment procedure; the problems with the entry flux management and macroscopic modeling framework.

TFT2016, Traffic Flow Theory and Characteristics Committee Summer Meeting, Sydney, AUSTRALIE, 02-/07/2016 - 03/07/2016; In this study we propose to analyze the effect of network heterogeneities on the prediction accuracy of a single reservoir model by comparison with a mesoscopic simulation of a simple network. We also investigate the influence of the average trip length choice on the simulation outputs.

Atelier des Plate-formes de l'IA : Jeux vidéos et IA, RENNES, FRANCE, 02-/07/2015 - 02/07/2015; Depuis maintenant plusieurs décennies, dans le domaine des transports terrestres, les simulateurs de conduite ont vu leur développement et leur utilisation se démocratiser. Ces simulateurs peuvent se décliner sous plusieurs configurations allant des plus complexes comme les simulateurs dynamiques 6-axes équipés d'écran semi cylindrique (1) aux plus simples comme les simulateurs de table équipés d'un seul écran et d'un volant (2). Aujourd'hui, d'autres simulateurs de déplacements ont vu le jour, comme des simulateur moto, vélo et de marche. Ces deux derniers genres restent encore assez confidentiels dans leur développement et leur diffusion. Les utilisations de ces simulateurs ont des objectifs qui peuvent majoritairement se classer en 3 catégories : " l'enrichissement des connaissances sur le comportement des sujets - le simulateur est utilisé pour mettre les sujets dans une situation pour étudier ses comportements comme par exemple la conduite dans le brouillard, le franchissement d'intersections ou la traversée de rue (3); " l'évaluation a priori de dispositifs - ces dispositifs peuvent aussi bien être des aménagements routiers que des systèmes d'aide à la conduite, dont on veut étudier l'impact sur les comportements (4); " l'apprentissage et la formation - pour ces applications, le simulateur est un médium pour l'acquisition et/ou la mobilisation des compétences du sujet par rapport à une situation ou une tâche donnée (5). Ces objets technologiques sont en évolution constante grâce aux progrès réalisés dans d'autres domaines, ce qui permet de dire qu'un simulateur de déplacements est une combinaison de technologies. Les axes de recherche et de développement concernent en majorité : 1) le visuel, tant par la qualité des images (la technologie High Dynamic Range par exemple (6)), que par les interfaces associées (utilisation des Head Mounted Displays) ; 2) la restitution du mouvement (accélérations longitudinales, transversales et verticales, (7)) ; et 3) le rendu sonore (auralisation). Si les simulateurs présentent de nombreux avantages, tel que le coût financier par rapport à des expérimentations en situation réelle, plusieurs freins viennent limiter leur essor. Le premier d'entre eux concerne la validité de ces outils. Malgré les nombreuses définitions autour du concept de validité, la question du transfert demeure : comment les résultats obtenus en simulation peuvent ils s'appliquer dans le monde réel ? Cette question dépasse les frontières du seul domaine des simulateur de déplacements. Une seconde limite concerne les interactions avec la scène virtuelle proposée aux sujets, et en particulier les interactions avec les personnages non joueurs (PNJ). La majorité des études réalisées sur simulateur de conduite le sont avec des PNJ scriptés, ie sans aucune autonomie. De fait les environnements proposés aux sujets sont souvent peu peuplés car la complexité des scénarios augmente avec le nombre de PNJ à coordonner. Pour certaines situations comme la conduite dans le brouillard ou la conduite de nuit sur autoroute, les situations ainsi simulées sont cohérentes avec celles que l'on peut rencontrer dans la vie réelle. Par certains aspects, les simulateurs de déplacements peuvent s'apparenter à des jeux sérieux numériques. L'utilisation de systèmes immersifs, la réalisation de consignes, la vue subjective (ou « vue à la première personne ») sont autant d'éléments que l'on peut retrouver dans l'élaboration de jeux sérieux. Les jeux sérieux numériques (digital serious games) sont devenus populaires dans les années 2000 (8). Leurs champs d'application sont très variés, allant des applications militaires à la psychiatrie (9) en passant par l'éducation. Une partie seulement des jeux sérieux utilisent des systèmes immersifs . Pour autant les progrès technologiques effectués ces dernières années notamment au niveau des interfaces visuelles (casques de réalité virtuelle) ouvrent de nouvelles perspectives, en particulier pour l'application à l'apprentissage et à la formation. L'objectif de cette contribution est de proposer deux sujets de discussion qui pourraient favoriser le rapprochement des communautés issues du monde des simulateurs de déplacements et des jeux vidéos. Le premier sujet concerne les interactions entre le sujet/joueur et les PNJ. Dans le domaine du transport terrestre, le sujet doit pouvoir interagir avec d'autres usagers des transports, en particulier les usagers de la route, qu'ils soient piétons, cyclistes ou conducteurs d'engins motorisés. Selon nous un peuplement de scènes crédible et fidèle aux phénomènes physiques de groupe observables (lois de trafic, comportement de foules..., etc.), avec lequel un joueur pourrait interagir, permettraient d'élargir la variété des environnements et d'offrir ainsi de nouvelles perspectives dans le domaine de l'apprentissage et de la formation par exemple. Une autre perspective serait de pouvoir considérer des espaces simulés plus vastes. Le second sujet concerne la validation des simulateurs et des jeux associés. Nous pouvons a minima distinguer deux types de validations . Le premier concerne le dispositif fourni au joueur/sujet. Un simulateur de conduite n'étant pas une voiture, une phase de familiarisation pour l'appropriation du dispositif est nécessaire. Les questions du contenu et de la durée de cette phase de familiarisation restent posées. Le second concerne les PNJ. Si les phénomènes physiques de groupes doivent être reproduits, la qualité individuelle des interactions doit également être reproduite (évitement de collision, conservation des liens de groupe pour des piétons, etc. ). On se place alors dans une approche multi-échelle pour la validation. Si de nombreux travaux existent déjà dans la littérature, des recherches supplémentaires sont nécessaires pour l'élaboration d'une méthodologie générique.

We propose a model of the driver perception suited for microscopic, agent-based traffic simulations. The model includes both top-down and bottom-up perception, and takes into account the limited amount of perceptive resource which gain access to short-term memory. The driving task is split into sub-tasks, which can be activated in parallel (e.g. car following and crossroads passing). Perceived entities (percepts) as well as subtasks are ranked with respect to their subjective value, and due to the bounded perception, only the more "valuable" percepts are sent to the decision module of the cognitive model. The competition among percepts to gain access to the short-term memory simulates attentional processes. A computational implementation of the model is proposed for the driver, using agent-based modeling. It is implemented in a traffic simulation environment and allows the driver-agent to manage the conflicts and the longitudinal space in the middle of the crossroads. This way, we improve the realism of the simulation. Furthermore, this model can lead to a new way of identifying and explaining near accidents. We illustrate some benefits for a microscopic traffic simulation at crossroads in two situations. The first scenario explores the traffic parameters at a crossroads, simulating various distributions of the driver's age. The second one demonstrates the adaptive behavior of simulated drivers facing a dangerous (e.g. hypo-vigilant) driver.; Nous proposons un modèle de perception pour la simulation de trafic microscopique, utilisant une architecture multi-agent. Le modèle traite la perception ascendante (bottom-up) et descendante (top-down), et simule le fait que seul un nombre limité d'entités perçues a accès à la mémoire à court terme, et donc au module de décision. La tâche de conduite est divisée en sous-tâches qui peuvent être actives simultanément (par exemple, suivi de véhicule et passage de carrefour). Les entités perçues (les "percepts") sont classées en fonction de leur valeur subjective pour le conducteur, et du fait des limites perceptives et attentionnelles, seuls les percepts les plus importants sont envoyés au module de décision du modèle cognitif. La compétition entre percepts pour accéder à la mémoire à court terme simule un processus attentionnel. Une implémentation computationnelle de ce modèle est proposée, utilisant un système multi-agent. Il est implémenté dans un environnement de simulation de trafic et permet au conducteur simulé de gérer les conflits et l'espace à l'intérieur du carrefour. Ce modèle permet notamment d'explorer et d'identifier des presque-accidents. Les bénéfices d'une simulation microscopique de l'intérieur des carrefours sont illustrés par des simulations, d'une part en simulant différentes distribution de l'âge des conducteurs, d'autre part en simulant l'adaptation des conducteurs à un comportement dangereux (hypo-vigilant).

We propose a model of the driver perception suited for microscopic, agent-based traffic simulations. The model includes both top-down and bottom-up perception, and takes into account the limited amount of perceptive resource which gain access to short-term memory. The driving task is split into sub-tasks, which can be activated in parallel (e.g. car following and crossroads passing). Perceived entities (percepts) as well as subtasks are ranked with respect to their subjective value, and due to the bounded perception, only the more "valuable" percepts are sent to the decision module of the cognitive model. The competition among percepts to gain access to the short-term memory simulates attentional processes. A computational implementation of the model is proposed for the driver, using agent-based modeling. It is implemented in a traffic simulation environment and allows the driver-agent to manage the conflicts and the longitudinal space in the middle of the crossroads. This way, we improve the realism of the simulation. Furthermore, this model can lead to a new way of identifying and explaining near accidents. We illustrate some benefits for a microscopic traffic simulation at crossroads in two situations. The first scenario explores the traffic parameters at a crossroads, simulating various distributions of the driver's age. The second one demonstrates the adaptive behavior of simulated drivers facing a dangerous (e.g. hypo-vigilant) driver.; Nous proposons un modèle de perception pour la simulation de trafic microscopique, utilisant une architecture multi-agent. Le modèle traite la perception ascendante (bottom-up) et descendante (top-down), et simule le fait que seul un nombre limité d'entités perçues a accès à la mémoire à court terme, et donc au module de décision. La tâche de conduite est divisée en sous-tâches qui peuvent être actives simultanément (par exemple, suivi de véhicule et passage de carrefour). Les entités perçues (les "percepts") sont classées en fonction de leur valeur subjective pour le conducteur, et du fait des limites perceptives et attentionnelles, seuls les percepts les plus importants sont envoyés au module de décision du modèle cognitif. La compétition entre percepts pour accéder à la mémoire à court terme simule un processus attentionnel. Une implémentation computationnelle de ce modèle est proposée, utilisant un système multi-agent. Il est implémenté dans un environnement de simulation de trafic et permet au conducteur simulé de gérer les conflits et l'espace à l'intérieur du carrefour. Ce modèle permet notamment d'explorer et d'identifier des presque-accidents. Les bénéfices d'une simulation microscopique de l'intérieur des carrefours sont illustrés par des simulations, d'une part en simulant différentes distribution de l'âge des conducteurs, d'autre part en simulant l'adaptation des conducteurs à un comportement dangereux (hypo-vigilant).

The aim of the communication is to address the opportunities of a street-crossing simulator to study the decisions and behaviors of older pedestrians in a safe and controlled environment. Older pedestrians are well-known to be over-involved in streetcrossing fatalities. For example, in France, people older than 75 years represent 37% of all pedestrians killed on the road, although they account for less than 9% of the population. For over one decade, pedestrian safety research has investigated age differences in street-crossing behaviors likely to, at least partially, account for the higher crash risk of older pedestrians. But some answers are still lacking and virtual reality can be useful in precisely examining the role of any specific traffic- or pedestrians-related characteristics. The original simulation device includes ten screens (2.55m x 1.88m) forming a corridor in which the pedestrian can actually walk up to 7 meters. The pedestrian's initial position is such that he can watch the traffic coming from both directions by turning his head to the left or right. He is standing at the edge of a sidewalk, facing the experimental street, and has to walk to the other side of the street when he thinks it is safe to do so. The images (60 frames per second) are calculated and projected at the participant’s eye height. Scenes are updated interactively by a movement-tracking system that records the participant’s locomotion (sub-millimeter accuracy) and head motion. A total of 18 young (age 19–35), 28 younger–old (age 62–71) and 38 older–old (age 72-85 years) adults recently participated in an experiment on such a device. The measure of precise behavioral indicators in terms of decision, movement and visual exploration revealed significant differences between the three age groups. The older-old participants crossed more slowly, adopted smaller safety margins, and made more decisions that led to collisions than did the both other groups of participants. Agerelated difficulties were found particularly when vehicles approached rapidly, or in the far lane. The present simulation device allows revealing dangerous attentional deficits as well as physical limitations in older pedestrians. The opportunities of the simulator to also train older people to increase the safety of their behaviors, as well to evaluate the effectiveness of pedestrian navigation aids can be also considered.

The expected future deployment of communication technologies, and the new generation of Intelligent Transportation Systems (ITS) known as cooperative systems bring lots of expectations in terms of vehicle traffic flow control and management. The numbers of interactions and exchanges between cars, and with the infrastructure can considerably grow, which as a result could carry new challenges to the traffic modeling community. In this paper we investigate the effects of cooperation between vehicles at a microscopic level, where communication is directly integrated into the car following law. Some linear stability analyses allow identifying regimes of potential propagation of shock waves into a traffic stream. Real data based simulation confirms the theoretical findings, and values of efficiency and safety indicators are discussed based on the chosen cooperative strategy.; Les avancées en technologies de la communication ont peu à peu donné naissance à une deuxième génération de Systèmes de transports intelligents (ITS) connus sous le nom de systèmes coopératifs. En permettant aux différents véhicules de communiquer entre eux ou à travers l'infrastructure, les systèmes coopératifs révolutionnent la gestion du trafic autant qu'ils la complexifient de par la richesse des possibilités qu'ils entrouvrent. L'implémentation prochaine de ces nouveaux services pose également un certain nombre de défis en modélisation du trafic qu'il convient d'anticiper. Dans cet article, nous proposons un effort d'intégration de quelques concepts de communication dans les modèles microscopiques de type loi de poursuite et les stratégies de changement de voie associées. Au niveau théorique, les analyses de stabilité montrent comment l'introduction d'une coopération permet, dans certaines situations, de limiter le développement d'ondes de type stop and go. Ces résultats sont ensuite illustrés en simulation à travers le calibrage de données réelles. Les expériences numériques permettent ainsi de conclure sur le potentiel stabilisant des systèmes coopératifs en situation de congestion. Des considérations sur le pourcentage de véhicules ou le rayon de communication permettent de fournir des premiers éléments d'aide à la décision en vue de futurs déploiements de ces nouvelles technologies.

International audience; The aim of this paper is to improve the validity of traffic simulations in urban and suburban fields, with a better consideration of the driving context and driver behavior in terms of anticipation of positioning on the lanes and occupation of space. Our model is based on a multi-agent approach and the emergence concept. The simulation intends to reproduce the observed behavior such as filtering between vehicles (two-wheels, emergency vehicles), prepositioning on lanes when approaching the road intersections, exceptional situations (stranded vehicle or improperly parked, etc.). The proposed approach considers that each driver is perceiving the situation in an ego-centered way and is readapting the road space by overriding the existing physical structure.

Pedestrian simulation is gaining more and more attention in recent years as demonstrated by the increasing number of pedestrians related paper in the literature. Whether this is for infrastructure design (stations, malls, etc.) or emergency evacuation, all fields are concerned. The different scales in modelling (macroscopic, microscopic) all have benefits and drawbacks. Several models exist in the pedestrian literature, most of them describing behaviours at a microscopic level. But no one deals with the coupling which can allow adaptation of the representation level to local needs. However, hybrid models begin to emerge in the road traffic field. The main goal of this paper is to present a first hybrid pedestrian model, given what exist in the road traffic field, by coupling a microscopic simulation model based on the Social Force Model of Helbing and the macroscopic traffic model LWR adapted to pedestrian simulation. This hybrid model would take the benefits of the two representation scales: being able to simulate a large network and having detailed information on specific nodes. The work is built on two main parts: the coupling of the macroscopic and the microscopic model on one side, and the calibration of the hybridization on another one. In the calibration part, the problems of compatibility is considered to elaborate several conditions at the transitions. This paper is a first work and is aimed at being completed in the future. The case of a unidirectional flow is investigated here and will further be updated to simulate a bidirectional flow.

Nowadays, micro-simulation is a common approach to study the behaviors of drivers in the road traffic. The main concern of most microscopic simulators is the network efficiency evaluation. The microsimulation approach relies on major models such as car following, lane changing and road crossing. Each of these models has a strong theoretical base, and corresponds to a specific road section and a specific driver's intention. Moreover, the micro-simulation approach can be used to investigate an accident or near accident situation. Some approaches tackle the individual behavior in these micro-simulations. For these approaches, a more detailed behavioral model, which is referred to the nanoscopic simulation, is required. In this paper, we focus on the road crossing behavior of drivers. Although various researches have been addressing this subject, existing approaches seem inadequate to simulate accurately drivers' behavior in the conflict area (the center of intersection) or in the crossroads exit. We are developing an active perception model following a nanoscopic approach, which will palliate this inadequacy. The aim of this paper is to make a qualitative comparison between our approach and the existing gap acceptance model. Our model allows to simulate the interaction between drivers at the center of intersection. Future work will consist in integrating the pedestrians in the road crossing scenario.

The simulation tools of people's displacements become more and more popular for applications emerging in the field of mobility planning, traffic management, impact assessment for city design and infrastructure modifications. Moreover, there is a lack of computational tools for the microscopic simulation of urban interactions between drivers and pedestrians. Feeling that road crossing is currently the main problem with pedestrian behavioural models, we conducted a laboratory experiment in order to understand to what extend the pedestrian's visual environment contribute to the crossing decision in order to improve a computational street crossing model. In the experiment, 36 12-second-video clips were presented to 32 participants, in conditions close to the crossing situation (scale 1, 160° of angle displayed on 6 large screens). The subjects were asked if they would have cross the street at the end of each clip. Two hypotheses were under investigation. The first one focuses on the objective description of the road crossing environment in terms of visual cues relevant for the crossing decision (traffic light, approaching vehicles, other pedestrians, etc.). The subject's answers were compared to the coding of the visual environment. The second hypothesis focuses on the subject's own explanations, about their motivations for crossing / not crossing. In both cases, the statistical analysis (logistic regressions) suggests that the crossing decision does not use the same visual cues depending of the presence/absence of traffic lights. The main result of this study is that the relevant visual cues are not the same at the signalized and at the unsignalized crossing, which leads to build separate quantitative models.

Les Systèmes Multi-Agents constituent désormais une des approches fréquemment utilisées dans un objectif de modélisation et de simulation de trafic routier. Des progrès restent toutefois à accomplir en vue d'améliorer le réalisme des comportements humains simulés, dont le comportement des conducteurs automobiles. En particulier, si le processus de décision a fait l'objet de nombreux travaux, le processus de perception a été relativement peu approfondi. Notre hypothèse est qu'une amélioration pourrait provenir de la prise en compte de la limitation de capacité de la perception simulée. Ce travail vise ainsi à intégrer un seuil de perception à un modèle d'agent afin d'étudier son influence sur le comportement global du trafic simulé.

Sommaire : Modélisation du trafic - Projet ARCHISIM - Plate-forme de simulation ARCHISIM et modèles de simulation associés - Simulation de situations de conduite - Usages - Applications -Synthèse et perspective