Simulating Pedestrian-Vehicle Interaction in an Urban Network Using Cellular Automata and Multi-Agent Models

Abhimanyu Godara (), Sylvain Lassarre () and Arnaud Banos ()
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Abhimanyu Godara: Banaras Hindu University, Dept. of Civil Eng., Institute of Technology
Sylvain Lassarre: Institut National De Recherche Sur Les Transports Et Leur Securite, GARIG
Arnaud Banos: University of Pau, SET Laboratory

A chapter in Traffic and Granular Flow’05, 2007, pp 411-418 from Springer

Abstract: Summary Agent-based and cellular automata models have been widely used in an efficient and effective way for studying granular traffic, but rarely considering the combined effect and interactions of pedestrians and vehicles in urban networks. So from this point of view an attempt has been made to develop a virtual urban environment which considers both vehicular and pedestrian traffic and the interactions arising from their behavior. This paper presents details of the model we have developed. For vehicular traffic a cellular automata model, combining and appropriately modifying (e.g. to account for the pedestrian movement) BML, NaSch and ChSch models, is considered. Pedestrian traffic is simulated using simple behavioral rules combined with an agent-based approach. Different constraints affecting the mobility of the whole system are considered, which can be seen and even changed by the user in the simulated environment. The model belongs to the microscopic category where pedestrians/vehicles behave in their environment by making a sequence of decisions. The interactions among vehicles and pedestrians are also incorporated which signifies various effects, ranging from accident risk of pedestrians to the generation of traffic jams. NetLogo which is a multi-agent based modeling language is used as the programming platform for the simulation.

Keywords: Cellular Automaton; Cellular Automaton; Intelligent Transportation System; Discrete Choice Model; Cellular Automaton Model (search for similar items in EconPapers)
Date: 2007
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DOI: 10.1007/978-3-540-47641-2_37

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