Swarm Intelligence Inspired Adaptive Traffic Control for Traffic Networks
- 632 Downloads
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.
KeywordsParticle swarm optimization Traffic signal control Adaptive control
This research was supported by the National Key Research and Development Program of China (2017YFB0102500).
- 4.Cao, L., Hu, B., Dong, X., et al.: Two intersections traffic signal control method based on ADHDP. In: IEEE International Conference on Vehicular Electronics and Safety. IEEE (2016)Google Scholar
- 6.Ren, Y., Wang, Y., Yu, G., et al.: An adaptive signal control scheme to prevent intersection traffic blockage. IEEE Trans. Intell. Transp. Syst. 18, 1519–1528 (2016)Google Scholar
- 10.Duan, H., Sun, C.: Swarm intelligence inspired shills and the evolution of cooperation. Sci. Reports 4(6), 5210 (2014)Google Scholar
- 11.Zhu, Y., Zhang, G., Qiu, J.: Network traffic prediction based on particle swarm BP neural network. J. Networks 8(11), 2685–2691 (2013)Google Scholar