A Risk-Driven Model for Traffic Simulation
Document type :
Communication dans un congrès avec actes
Title :
A Risk-Driven Model for Traffic Simulation
Author(s) :
Nongaillard, Antoine [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Systèmes Multi-Agents et Comportements [SMAC]
Mathieu, Philippe [Auteur]
Systèmes Multi-Agents et Comportements [SMAC]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Systèmes Multi-Agents et Comportements [SMAC]
Mathieu, Philippe [Auteur]
Systèmes Multi-Agents et Comportements [SMAC]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Scientific editor(s) :
Dong, Yucheng
Herrera-Viedma, Enrique
Matsui, Kenji
Omatsu, Shigeru
Gonzàlez Briones, Alfonso
Rodriguez Gonzàlez, Sara
Herrera-Viedma, Enrique
Matsui, Kenji
Omatsu, Shigeru
Gonzàlez Briones, Alfonso
Rodriguez Gonzàlez, Sara
Conference title :
Distributed Computing and Artificial Intelligence, 17th International Conference, {DCAI} 2020,
City :
L'Aquila
Country :
Italie
Start date of the conference :
2020-06-17
Journal title :
Advances in Intelligent Systems and Computing
Publisher :
Springer International Publishing
Publication date :
2021
HAL domain(s) :
Informatique [cs]/Intelligence artificielle [cs.AI]
Informatique [cs]/Système multi-agents [cs.MA]
Informatique [cs]/Modélisation et simulation
Informatique [cs]/Système multi-agents [cs.MA]
Informatique [cs]/Modélisation et simulation
English abstract : [en]
With the advent of the autonomous vehicle and the transformation appearing in the automobile sector in the next decade, road traffic simulation has taken off again. In particular, it is one of the few ways to test an ...
Show more >With the advent of the autonomous vehicle and the transformation appearing in the automobile sector in the next decade, road traffic simulation has taken off again. In particular, it is one of the few ways to test an autonomous vehicle in silico [6]. To achieve this, current traffic generators must increase their realism. We argue here that one of the major points of this realism concerns the consideration of risk in driving models. We propose here an individual and self-organizing driving model based on customisable risk-taking factors. In this model, interactions create accidents. Each driver, individually, does not generate any accident, but the collectivity does. Accidents here are unpredictable emerging phenomena resulting from individual deterministic behaviours. Thanks to this model, the risk-taking factor of vehicles improves the realism of the simulations.Show less >
Show more >With the advent of the autonomous vehicle and the transformation appearing in the automobile sector in the next decade, road traffic simulation has taken off again. In particular, it is one of the few ways to test an autonomous vehicle in silico [6]. To achieve this, current traffic generators must increase their realism. We argue here that one of the major points of this realism concerns the consideration of risk in driving models. We propose here an individual and self-organizing driving model based on customisable risk-taking factors. In this model, interactions create accidents. Each driver, individually, does not generate any accident, but the collectivity does. Accidents here are unpredictable emerging phenomena resulting from individual deterministic behaviours. Thanks to this model, the risk-taking factor of vehicles improves the realism of the simulations.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :