Paper Info
Title
Swarm Intelligence Inspired Adaptive Traffic Control for Traffic Networks.
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.
Year
DOI
Venue
2017
10.1007/978-3-319-74176-5_1
Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering
Keywords
DocType
Volume
Particle swarm optimization,Traffic signal control,Adaptive control
Conference
221
ISSN
Citations 
PageRank 
1867-8211
0
0.34
References 
Authors
1
9
Name
Order
Citations
PageRank
Daxin Tian120432.49
Wei Yu210613.39
Jianshan Zhou312913.66
Kunxian Zheng472.49
Xuting Duan5264.92
Yunpeng Wang619425.34
WenYang Wang700.34
Rong Hui800.34
Peng Guo92916.63