Research Article
Swarm Intelligence Inspired Adaptive Traffic Control for Traffic Networks
@INPROCEEDINGS{10.1007/978-3-319-74176-5_1, author={Daxin Tian and Yu Wei and Jianshan Zhou and Kunxian Zheng and Xuting Duan and Yunpeng Wang and Wenyang Wang and Rong Hui and Peng Guo}, title={Swarm Intelligence Inspired Adaptive Traffic Control for Traffic Networks}, proceedings={Industrial Networks and Intelligent Systems. 3rd International Conference, INISCOM 2017, Ho Chi Minh City, Vietnam, September 4, 2017, Proceedings}, proceedings_a={INISCOM}, year={2018}, month={1}, keywords={Particle swarm optimization Traffic signal control Adaptive control}, doi={10.1007/978-3-319-74176-5_1} }- Daxin Tian
Yu Wei
Jianshan Zhou
Kunxian Zheng
Xuting Duan
Yunpeng Wang
Wenyang Wang
Rong Hui
Peng Guo
Year: 2018
Swarm Intelligence Inspired Adaptive Traffic Control for Traffic Networks
INISCOM
Springer
DOI: 10.1007/978-3-319-74176-5_1
Abstract
The internet of Vehicles (IoV) technologies have boosted diverse applications related to Intelligent Transportation System (ITS) and Traffic Information Systems (TIS), which have significant potential to advance management of complex and large-scale traffic networks. With the goal of adaptive coordination of a traffic network to achieve high network-wide traffic efficiency, this paper develops a bio-inspired adaptive traffic signal control for real-time traffic flow operations. This adaptive control model is proposed based on swarm intelligence, inspired from particle swarm optimization. It treats each signalized traffic intersection as a particle and the whole traffic network as the particle swarm, then optimizes the global traffic efficiency in a distributed and on-line fashion. Our simulation results show that the proposed algorithm can achieve the performance improvement in terms of the queuing length and traffic flow allocation.
