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Affordance-based agent model for road traffic simulation

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Abstract

Existing traffic simulations often consider normative driver behavior. Drivers do not always use physically delineated lanes: sometimes drivers use the entire road surface. Thus, current traffic simulations do not reproduce all observed urban and suburban traffic phenomena. To improve the validity of urban and suburban traffic simulations, we propose to consider driving context and driver behavior in terms of occupied space. We endow driver agents with an ego-centered representation of the environment based on the concept of affordances and virtual lanes. Affordances thus identify the possible space occupation actions afforded by the environment and by other agents. The proposed model was implemented using our ArchiSim tool. We show that this model is more efficient and realistic than existing models. The experiments also reproduce real traffic situations and compare simulated data to real data.

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Notes

  1. The French National Institute for Transport and Safety Research (ex-INRETS).

  2. The distance to the norm (traffic rules) is randomly specified during agent initialization; it denotes the degree of compliance with norms and ensures heterogeneity for the agents.

  3. This function choice is completely empirical: we chose the parameters that affect agent behavior based on psychological studies.

  4. The expected agent speed in lane \(VV_{j}\) is given by the weighted sum of the parameters mentioned below.

  5. French acronym for “The Environment and Energy Management Agency”

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Acknowledgments

This research was partially funded by the French Ministry of Education, Research and Technology, the Nord/Pas-de-Calais Region, the CNRS and the International Campus on Safety and Intermodality in Transportation (CISIT). We would like also to thank the anonymous reviewers for their comments.

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Authors and Affiliations

  1. LAMIH UMR CNRS 8201, Université de Valenciennes, F-59313 , Valenciennes, France

    Feirouz Ksontini & René Mandiau

  2. LIP6, MAS Team, 4 place Jussieu, F-75005 , Paris, France

    Zahia Guessoum

  3. IFSTTAR, TS2-SIMU, 14-20 bd Newton, F-77447 , Marne la Vallée Cedex 2, France

    Feirouz Ksontini & Stéphane Espié

Authors
  1. Feirouz Ksontini
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  2. René Mandiau
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  3. Zahia Guessoum
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  4. Stéphane Espié
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Correspondence to René Mandiau.

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Ksontini, F., Mandiau, R., Guessoum, Z. et al. Affordance-based agent model for road traffic simulation. Auton Agent Multi-Agent Syst 29, 821–849 (2015). https://doi.org/10.1007/s10458-014-9269-x

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