Emergent behaviors and traffic density among heuristically-driven intelligent vehicles using V2V communication
2014 International Conference on Connected Vehicles and Expo (ICCVE)(2014)
摘要
In this paper, we study the global traffic density and emergent traffic behavior of several hundreds of intelligent vehicles, as a function of V2V communication (for the ego vehicle to perceive traffic) and path-finding heuristics (for the ego vehicle to reach its destination), in urban environments. Ideal/realistic/no V2V communication modes are crossed with straight-line/towards-most-crowded/towards-least-crowded path-finding heuristics to measure the average trip speed of each vehicle. The behaviours of intelligent vehicles are modelled by a finite state automaton. The V2V communication model is also built based on signal propagation models in an intersection scenario and a Markov-chain based MAC model. Our experiments in simulation over up to 400 vehicles exhibit attractive insights: 1) communication's impact is positive for the performance of the emergent vehicles' behaviour, however, 2) the path-finding heuristics may not obtain their expected collective behaviour due to the communications errors in realistic road environment.
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关键词
intelligent vehicles,path-finding heuristics,V2V communication model,Markov-chain based MAC model,signal propagation models,finite state automaton
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