Traffic Behavioral Simulation in Urban and Suburban – Representation of the Drivers’ Environment

Ksontini, Feirouz; Éspié, Stéphane; Guessoum, Zahia; Mandiau, René

doi:10.1007/978-3-642-28786-2_13

Cited by 7 publications

(4 citation statements)

References 9 publications

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“…Espie´and Auberlet 2007show that standard car-following models lack anticipation beyond the immediately preceding entity for showing realistic behaviour especially in situations with ramp lanes. Their simulation model ARCHISIM allows complex agent-centric perception for realistic driving models; recent versions focus on realistic environmental representation involving also the perception of non-standard situations with emergency vehicles or unexpected obstacles (Ksontini et al, 2012). Traffic accidents and improvement of pedestrian safety also motivate the work of Waizman et al (2012) who use a 3D model with detailed agent manoeuvre behaviour and analysis of driver or pedestrian agents perception.…”

Section: Agent-based Traffic Flow Simulationmentioning

confidence: 99%

A review on agent-based technology for traffic and transportation

Bazzan

Klügl

2013

The Knowledge Engineering Review

237

117

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In the last few years, the number of papers devoted to applications of agent-based technologies to traffic and transportation engineering has grown enormously. Thus, it seems to be the appropriate time to shed light over the achievements of the last decade, on the questions that have been successfully addressed, as well as on remaining challenging issues. In the present paper, we review the literature related to the areas of agent-based traffic modelling and simulation, and agent-based traffic control and management. Later we discuss and summarize the main achievements and the challenges.

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Section: Agent-based Traffic Flow Simulationmentioning

confidence: 99%

A review on agent-based technology for traffic and transportation

Bazzan

Klügl

2013

The Knowledge Engineering Review

237

117

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“…Another research project concerns the ARCHISIM simulator (Espié & Auberlet, 2007) which models in a realistic way the perception and reasoning process of human drivers, which includes their model of the behavior of surrounding vehicles. More recent work extends this model to the way human drivers anticipate special situations, such as the movement of emergency vehicles, motorcycles, improperly parked vehicles and so on (Ksontini et al, 2012). (Benenson et al, 2008) describe an agent based model of parking in the city, which includes both physical models of speed, as well as cognitive models of the agent which involves decision making about high level factors such as the cost of parking, the distance to home and the time spent in looking for the parking spots.…”

Section: Agent-based Traffic Flow Simulationmentioning

confidence: 98%

Modeling the Strategic Behavior of Drivers for Multi-Lane Highway Driving

Luo

Turgut

Bölöni

2014

Journal of Intelligent Transportation Systems

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Current state-of-the-art highway traffic flow simulators rely extensively on models using formulas similar to those describing physical phenomena such as forces, viscosity or potential fields. These models have been carefully calibrated to represent the overall flow of traffic and they can also be extended to account for the cognitive limitations of the driver, such as reaction times. However, there are some aspects of driver behavior such as strategic planning which are difficult to formulate mathematically. In this paper, we describe the YAES-DSIM highway simulator which integrates virtual physics models with an agent-based model. The virtual physics component models the physical vehicle and the subconscious aspects of the driver behavior, while the agent component is responsible for the strategic and tactical decisions which are difficult to model using virtual physics. In this paper we focus on the lane change decisions of the drivers, with special attention to the optimal lane positioning for a safe exit. We have used the model to simulate the flow of traffic on Highway 408 in Orlando, Florida and to study the impact of various tactical and strategic decisions on the efficiency and safety of the traffic.

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“…Pour évaluer les comportements individuels des agents en termes de positionnement dans l'espace routier, nous utilisons différents scénarii permettant de placer les agents dans des situations de trafic appropriées pour observer le comportement désiré. Nous proposons une validation se basant sur le comportement habituel de déplacement des deux-roues [42,46]. Le scénario proposé dans ce cadre, vise à reproduire un comportement que nous observons souvent dans la réalité : une remontée de file au niveau d'un carrefour avec tourner à gauche et à droite.…”

Section: Validationunclassified

“…Nous pouvons ajouter que notre modèle prend en compte le fait que la pratique du faufilement est mieux tolérée pour les deux-roues motorisés que pour les autres types de véhicules. D'autres travaux que nous avons effectués [46] montrent que le conducteur de la voiture choisit la solution d'une voie virtuelle uniquement s'il a un comportement non normatif (cas extrême). Le choix des voies virtuelles n'est pas systématique, il dépend des caractéristiques des voies ainsi que des caractéristiques du véhicule (la taille par exemple) et des caractéristiques individuelles des agents (la distance par rapport à la réglementation).…”

Section: Comparaison Entre Les Données Réelles Et Les Données Simuléesunclassified

Représentation ego-centrée à base d’affordances de l’environnement pour la simulation multi-agents de trafic

Ksontini¹,

Mandiau

Guessoum³

et al. 2016

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Afin d'améliorer la validité des simulations de trafic en milieux urbain et péri-urbain, nous proposons un nouveau modèle d'agent permettant de mieux prendre en compte le contexte de conduite et les comportements des conducteurs en termes d'occupation de l'espace. Le but est de produire en simulation des comportements observés en situation réelle tels que les phénomènes de faufilement (2 roues, véhicules d'urgence). Nous dotons l'agent d'une représentation ego-centrée de l'environnement fondée sur le concept des affordances. Nous utilisons ainsi les affordances pour identifier les actions possibles, en termes d'occupation de l'espace (voies virtuelles), offertes par l'environnement. Nous les utilisons ensuite pour construire une représentation ego-centrée de la situation. Le modèle d'agent proposé a été implémenté avec ArchiSim. Cette implémentation a permis de reproduire une situation de trafic réelle et de comparer les données simulées avec celles recueillies sur le terrain. Mots clés simulation multi-agents • affordances • simulation de trafic • voies virtuelles Abstract To improve the validity of traffic simulations in urban and suburban areas, we propose to consider the driving context and the driver behavior in terms of space occupation. We endow agent driver with an ego-centered

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Traffic Behavioral Simulation in Urban and Suburban – Representation of the Drivers’ Environment

Cited by 7 publications

References 9 publications

A review on agent-based technology for traffic and transportation

A review on agent-based technology for traffic and transportation

Modeling the Strategic Behavior of Drivers for Multi-Lane Highway Driving

Représentation ego-centrée à base d’affordances de l’environnement pour la simulation multi-agents de trafic

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