Urban Traffic and the Environment

Simulation of traffic flow on non-uniform road sections with cellular automaton model

Expand
  • 1. Shanghai Institute of Applied Mathematics and Mechanics, School of Mechanics and Engineering Science, Shanghai University, Shanghai 200072, China
    2. Shanghai Key Laboratory of Mechanics in Energy Engineering, Shanghai 200072, China

Received date: 2022-03-31

  Online published: 2022-08-29

Abstract

Traffic flow characteristics on non-uniform road sections under traffic light controls were investigated using a refined velocity-dependent-randomization (VDR) model, considering three traffic light strategies: in-phase, anti-phase, and self-organizing. The effects of traffic light strategies on road traffic efficiency are analyzed under the periodic boundary. The simulation results show that for uniform road sections, the green wave phenomenon occurs at low densities using in-phase and anti-phase traffic light strategies. It was found that the traffic flow under the in-phase strategy is insensitive to variation in road length. In contrast, the traffic flow under the anti-phase strategy is sensitive to variation in road length, and the green wave phenomenon is suppressed, particularly when a short road section is significantly smaller than the average road length. Under the self-organizing traffic light strategy, fundamental diagrams are insensitive to variations in road length. Moreover, the traffic efficiency on the multi-section road is significantly improved, and the green wave phenomenon is replicated within a specific density range.

Cite this article

ZHOU Wenhai, LI Shujian, DONG Liyun . Simulation of traffic flow on non-uniform road sections with cellular automaton model[J]. Journal of Shanghai University, 2022 , 28(4) : 594 -607 . DOI: 10.12066/j.issn.1007-2861.2391

References

[1] Nagel K, Schreckenberg M. A cellular automaton model for freeway traffic[J]. Journal de Physique Ⅰ, 1992, 2(12): 2221-2229.
[2] Barlovic R, Santen L, Schadschneider A, et al. Metastable states in cellular automata for traffic flow[J]. The European Physical Journal B, 1998, 5: 793-800.
[3] Jiang R, Wu Q S. A stopped time dependent randomization cellular automata model for traffic flow controlled by traffic light[J]. Physica A, 2006, 364: 493-496.
[4] 李盛春, 孔令江, 刘慕仁, 等. 智能交通灯对交叉路口的交通灯影响[J]. 物理学报, 2009, 58(4): 2266-2270.
[5] 郑容森, 吕集尔, 朱留华, 等. 主干道交通流的路口效应[J]. 物理学报, 2009, 58(8): 5244-5250.
[6] Mhirch A. The effect of traffic light on accident probability in open and periodic boundaries system[J]. Physica A, 2015, 434: 226-231.
[7] Aleko D R, Djahel S. An efficient adaptive traffic light control system for urban road traffic congestion reduction in smart cities[J]. Information, 2020, 11 (2): 119.
[8] Gershenson C. Self-organizing traffic lights[J]. Complex Systems, 2005, 16: 29-53.
[9] Gershenson C, Rosenblueth D A. Adaptive self-organization vs static optimization: a qualitative comparison in traffic light coordination[J]. Kybernetes, 2012, 41(3/4): 386-403.
[10] Gershenson C, Rosenblueth D A. Self-organizing traffic lights at multiple-street intersections[J]. Complexity, 2012, 17(4): 23-39.
[11] Cesme B, Furth P G. Self-organizing traffic signals using secondary extension and dynamic coordination[J]. Transportation Research Part C, 2014, 48: 1-15.
[12] Zapotecatl J L, Rosenblueth D A, Gershenson C. Deliberative self-organizing traffic lights with elementary cellular automata[J]. Complexity, 2017, 2017(5): 1-15.
[13] Zou G, Yilmaz L. Self-organization models of urban traffic lights based on digital infochemicals[J]. Simulation, 2019, 95(3): 271-285.
[14] Brockfeld E, Barlovic R, Schadschneider A, et al. Optimizing traffic lights in a cellular automaton model for city traffic[J]. Physical Review E, 2001, 64(5): 56132.
[15] Chowdhury D, Schadschneider A. Self-organization of traffic jams in cities: effects of stochastic dynamics and signal periods[J]. Physical Review E, 1999, 59(2): R1311
Outlines

/