收稿日期: 2022-03-31
网络出版日期: 2022-08-29
基金资助
国家自然科学基金资助项目(11572184)
Simulation of traffic flow on non-uniform road sections with cellular automaton model
Received date: 2022-03-31
Online published: 2022-08-29
基于细化的 VDR(velocity-dependent-randomization) 模型研究了交通灯控制下非均匀路段道路交通流的演化特征, 并在周期边界下讨论了同相、反相和自组织 3 种交通灯策略对道路通行效率的影响. 模拟结果表明: 对于均匀路段, 低密度下采用同相和反相策略都会出现绿波现象. 同相策略时交通流对路段长度变化不敏感, 而反相时则影响明显, 尤其是存在明显小于平均路长的短路段, 绿波现象也会受到抑制. 在自组织交通灯策略下, 路段交通流对于路段长度变化不敏感, 道路通行效率明显提高, 并在一定密度范围内再现绿波现象.
周文海, 李舒健, 董力耘 . 非均匀路段交通流的元胞自动机模拟[J]. 上海大学学报(自然科学版), 2022 , 28(4) : 594 -607 . DOI: 10.12066/j.issn.1007-2861.2391
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.
| [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 |
/
| 〈 |
|
〉 |
