Research Article
Adaptive Traffic Signal Coordinated Timing Decision for Adjacent Intersections with Chicken Game
@INPROCEEDINGS{10.1007/978-3-319-93710-6_25, author={Xin-hai Xia}, title={Adaptive Traffic Signal Coordinated Timing Decision for Adjacent Intersections with Chicken Game}, proceedings={Intelligent Transport Systems -- From Research and Development to the Market Uptake. First International Conference, INTSYS 2017, Hyvink\aa{}\aa{}, Finland, November 29-30, 2017, Proceedings}, proceedings_a={INTSYS}, year={2018}, month={7}, keywords={Adaptive traffic signal timing Intersection Chicken game Decision}, doi={10.1007/978-3-319-93710-6_25} }
- Xin-hai Xia
Year: 2018
Adaptive Traffic Signal Coordinated Timing Decision for Adjacent Intersections with Chicken Game
INTSYS
Springer
DOI: 10.1007/978-3-319-93710-6_25
Abstract
Adaptive traffic signal timing decision is a promising technique to alleviate traffic congestion which is an issue in every major city. An interesting problem is to study the traffic signal timing decision on an intersection, that is an important aspect of the urban traffic control system. According to the mutual relevance of traffic flow between intersections and the theoretical framework of chicken game, traffic signal timing decision model based on chicken game was proposed for two adjacent intersections. Each intersection was defined as a game player and the queue length of the whole intersection was regarded as payoff function. Nash equilibrium of mixed strategies was obtained based on the chicken game model which belongs to a non-cooperative game, so the state of signal light in next game-cycle can be on-line adjusted. The digital characteristics and effectiveness of the proposed method was analyzed. Simulation results showed that the game-based method substantially outperforms the other non-coordinated method like fixed timing control. The queue length of the intersection and the total vehicle travel time and topping number at each section can be effectively improved using the proposed algorithm.