HU Wenbin, WANG Huan, YAN Liping, DU Bo. A Hybrid Cellular Swarm Optimization Method for Traffic-Light Scheduling[J]. Chinese Journal of Electronics, 2018, 27(3): 611-616. doi: 10.1049/cje.2018.02.002
Citation: HU Wenbin, WANG Huan, YAN Liping, DU Bo. A Hybrid Cellular Swarm Optimization Method for Traffic-Light Scheduling[J]. Chinese Journal of Electronics, 2018, 27(3): 611-616. doi: 10.1049/cje.2018.02.002

A Hybrid Cellular Swarm Optimization Method for Traffic-Light Scheduling

doi: 10.1049/cje.2018.02.002
Funds:  This work is supported by the National Natural Science Foundation of China (No.61572369, No.70901060, No.711530238) and the Hubei Province Natural Science Foundation (No.2015CFB423, No.2014CFB193).
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  • Corresponding author: WANG Huan (corresponding author) is currently a Ph.D. candidate. His main research interests are intelligent traffic simulation and optimization and social network analysis. (
  • Received Date: 2015-11-27
  • Rev Recd Date: 2016-02-19
  • Publish Date: 2018-05-10
  • With increasing traffic every day, most cities in the world are facing serious traffic problems, such as traffic accidents, congestion and air pollution. Despite the recent improvement of urban infrastructure, reasonable traffic light scheduling still plays an important role in alleviating these traffic problems. It is a great challenge to schedule a huge number of traffic lights efficiently. To solve this problem, we propose a Hybrid cellular swarm optimization method (HCSO) to optimize the scheduling of urban traffic lights. HCSO achieves an efficient and flexible scheduling, which includes the phase timing scheduling and the phase shifting scheduling. To formulate effective solutions for various traffic problems and achieve a globally dynamic scheduling, flexible and concise transition rules based on Cellular automaton (CA) are defined. And the Dynamic cellular particle swarm optimization algorithm (DCPSO) is proposed to find the optimal phase timing scheduling efficiently. Moreover, compared with the differential search algorithm method, the genetic algorithm method, the particle swarm optimization method, the comprehensive learning particle swarm optimization method and the random method in real cases, extensive experiments reveal that HCSO achieves obvious improvements under different traffic conditions.
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  • De Oliveira, M.B.W. Areolino and D.A.N. Areolino, "Optimization of traffic lights timing based on artificial neural networks", IEEE 17th International Conference on Intelligent Transportation Systems (ITSC), Qingdao, China, pp.1921-1922, 2014.
    Hu W, Yan L, Liu K, et al., "A short-term traffic flow forecasting method based on the hybrid PSO-SVR", Neural Processing Letters, Vol.43, No.1, pp.155-172, 2016.
    H. Sun, J. Wu, W. Wang, et al., "Reliability-based traffic network design with advanced traveler information systems", Transport, Vol.287, pp.121-139, 2014.
    A. Tirachini, D.A. Hensher and J.M. Rose, "Multimodal pricing and optimal design of urban public transport:The interplay between traffic congestion and bus crowding", Transportation Research Part B:Methodological, Vol.61, No.2, pp.33-54, 2014.
    K. Shaaban and I. Kim, "Comparison of SimTraffic and VISSIM microscopic traffic simulation tools in modeling roundabouts", Procedia Computer Science, Vol.52, No.1, pp.43-50, 2015.
    S. Koyama, N. Shinozaki and S. Morishita, "Modeling of walking by cellular automata based on crowd flow model", Journal of Environmental Engineering, Vol.78, No.691, pp.669-677, 2013.
    R. Jiang, M.B. Hu, B. Jia, et al., "A new mechanism for metastability of under-saturated traffic responsible for timedelayed traffic breakdown at the signa", Computer Physics Communications, Vol.185, No.5, pp.1439-1442, 2014.
    Z. Sun, Z. Chen, H. Hu, et al., "Ship interaction in narrow water channels:A two-lane cellular automata approach", Physica A:Statistical Mechanics and Its Applications, Vol.431, pp.46-51, 2015.
    Hu Wenbin, H. Wang and Z. Min, "A storage allocation algorithm for outbound containers based on the outer-inner cellular automaton", Information Sciences, Vol.281, pp.147-171, 2014.
    J. Garcia-Nieto, E. Alba, A. Carolina Olivera, et al., "A Swarm intelligence for traffic light scheduling:Application to real urban areas", Engineering Applications of Artificial Intelligence, Vol.25, No.2, pp.274-283, 2014.
    Z. Beheshti, S.M. Shamsuddin and S. Hasan, "Memetic binary particle swarm optimization for discrete optimization problems", Information Sciences, Vol.299, pp.58-84, 2015.
    SM Elsayed, RA Sarker, and E. Mezura-Montes, "Self-adaptive mix of particle swarm methodologies for constrained optimization", Information Sciences, Vol.277, pp.216-233, 2014.
    S.W. Chiou, "Optimal signal-setting for road network with maximum capacity", Information Sciences, Vol.273, No.8, pp.287-303, 2014.
    J. Raphael, S. Maskell and E. Sklar, "From goods to traffic:First steps toward an auction-based traffic signal controller", Advances in Practical Applications of Agents, Multi-Agent Systems, and Sustainability:The PAAMS Collection, Springer International Publishing, pp.187-198, 2015.
    H. Wang, W. Hu, Z. Qiu, et al., " Nodes' evolution diversity and link prediction in social networks", IEEE Transactions on Knowledge and Data Engineering, Vol.29, No.10, pp.2263-2274, 2017.
    K. Udagepola, B.A. Alshami, N. Afzal, et al., "An adaptive controller of traffic lights using genetic algorithms", Progress in Systems Engineering Advances in Intelligent Systems and Computing, Springer International Publishing, pp.669-672, 2015.
    M. Collotta, L.L. Bello and G. Pau, "A novel approach for dynamic traffic lights management based on wireless sensor networks and multiple fuzzy logic controllers", Expert Systems with Applications, Vol.42, No.13, pp.5403-5415, 2015.
    H. Homaei, S.R. Hejazi and S.A.M. Dehghan, "Traffic light controller using fuzzy logic for a full single junction involving emergency vehicle preemption", Journal of Uncertain Systems, Vol.9, No.1, 2013.
    C. Ozan, O. Baskan, S. Haldenbilen, et al., "A modified reinforcement learning algorithm for solving coordinated signalized networks", Transportation Research Part C:Emerging Technologies, Springer International Publishing, Vol.54, pp.40-55, 2015.
    Y. Shi, H. Liu, L. Gao, et al., "Cellular particle swarm optimization", Information Sciences, Vol.181, No.20, pp.4460-4493, 2011.
    J. Liu, K.L. Teo, X. Wang, et al., "An exact penalty functionbased differential search algorithm for constrained global optimization", Soft Computing, Vol.20, No.4, pp.1305-1313, 2016.
    S. Kachroudi, "A multimodal traffic responsive strategy using particle swarm optimization", Control in Transportation System, Vol.42, pp.531-537, 2009.
    W. Hu, H. Wang, L. Yan, et al., "A swarm intelligent method for traffic light scheduling:Application to real urban traffic networks", Applied Intelligence, Vol.44, No.1, pp.1-24, 2015.
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