A Cellular Automaton Model for Highway: Considering Multi-Lane Traffic Rules
Hong Zhu, Dan Wang, Jibiao Zhou
Abstract
Hong Zhu, Dan Wang, Jibiao Zhou
Abstract
Vehicular flow in highway is inherently complex and development of microscopic models of vehicular flow has been a daunting task for researchers. This paper presents the use of Cellular automata (CA) micro simulation for modeling multi-lane traffic characteristics in highway, as well as considering the average speed difference (ASD) and lane-changing rules (LCR) in the CA model. Firstly, on the base of the Symmetric Two-Lane Cellular Automata (STCA) model, we analyzed the impact on traffic characteristics, through adjusting the maximum speed and lane-changing rules. Secondly, by the micro simulation, the relationships between speed and density in traffic flow were given considering the ASD and the LCR. The simulation results showed that, (a) the more obvious of speed dispersion, the more serious about speed declining, (b) the speed of overall traffic flow slowed down by 163% under extreme conditions, (c) the more reckless of lane-changing rule drivers used, the higher speed of traffic flow can reach.
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Vehicular flow in highway is inherently complex and development of microscopic models of vehicular flow has been a daunting task for researchers. This paper presents the use of Cellular automata (CA) micro simulation for modeling multi-lane traffic characteristics in highway, as well as considering the average speed difference (ASD) and lane-changing rules (LCR) in the CA model. Firstly, on the base of the Symmetric Two-Lane Cellular Automata (STCA) model, we analyzed the impact on traffic characteristics, through adjusting the maximum speed and lane-changing rules. Secondly, by the micro simulation, the relationships between speed and density in traffic flow were given considering the ASD and the LCR. The simulation results showed that, (a) the more obvious of speed dispersion, the more serious about speed declining, (b) the speed of overall traffic flow slowed down by 163% under extreme conditions, (c) the more reckless of lane-changing rule drivers used, the higher speed of traffic flow can reach.
Key concepts: Cellular automaton, Traffic flow (computer networking), Flow (mathematics), Computer science, Simulation, Microscopic traffic flow model, Task (project management), Dispersion (optics)