吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (1): 89-97.doi: 10.13229/j.cnki.jdxbgxb20161255

• 论文 • 上一篇    下一篇

信号交叉口自行车和行人混合交通流社会力模型

王占中, 赵利英, 焦玉玲, 曹宁博   

  1. 吉林大学 交通学院,长春 130022
  • 收稿日期:2016-12-12 出版日期:2018-02-26 发布日期:2018-02-26
  • 通讯作者: 焦玉玲(1968-),女,副教授.研究方向:物流系统设施设备规划与设计.E-mail: jyling777@163.com
  • 作者简介:王占中(1965-),男,教授,博士生导师.研究方向:运输资源优化技术.E-mail: wangzz@jlu.edu.cn
  • 基金资助:
    国家自然科学基金项目(51578262)

Social force model of pedestrian-bike mixed flow at signalized crosswalk

WANG Zhan-zhong, ZHAO Li-ying, JIAO Yu-Ling, CAO Ning-bo   

  1. College of Transportation, Jilin University, Changchun, 130022, China
  • Received:2016-12-12 Online:2018-02-26 Published:2018-02-26

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摘要： 基于行人仿真的社会力模型,考虑自行车对行人过街的干扰,引入自行车与行人以及自行车与人行横道间的相互作用,提出了一种改进的自行车和行人混合交通流的社会力模型。通过数值模拟,分析了自行车道的设置对混合交通流事故数及到达率的影响,再现了自行车和行人混合交通流中自行车的跟随和分层现象。仿真结果表明:设置自行车道能够有效缓解行人和自行车之间的冲突,有助于减少行人和自行车的事故数并提高混合交通流的运行效率;根据自行车数量,设置合理的自行车道,能够保证自行车达到最大过街速度,从而提高自行车的过街效率;模型能够重现混合交通流的自组织等现象。

关键词: 交通运输系统工程, 社会力模型, 自行车, 行人, 混合交通

Abstract: Based on basic social force model, considering the interference of bikes on pedestrian, this paper presents a modified social force model to describe the interactions between bikes and pedestrians. By simulation, the influences of the setting cyclists' path on the number of pedestrians and bicycle accidents and the arrival rate of bicycles were analyzed; and then, the slipstreaming, self-organization and lane-forming of bicycle and pedestrian mixed flow were reproduced, which obeys the observed data. The simulation results show that setting of cyclists' path can effectively alleviate the conflicts of bicycles and pedestrians, and help to reduce the number of potential traffic accidents of pedestrian and bicycle mixed flow, thus, improving the operation efficiency of the mixed traffic flow. Comparison of the simulation results and the observed data proves the effectiveness of the modified model. Besides, conclusions are drawn that with the increase of bicycle traffic, setting the cyclists' path on the crosswalk becomes more beneficial. Furthermore, setting wider cyclists' path according to the bicycle volume can guarantee bicycles to cross the crosswalk with maximum speed. The simulation model enables us to visually represent pedestrian and cyclist collective phenomenon.

Key words: engineering of communications and transportation system, social force model, bike, pedestrian, mixed traffic flow

中图分类号: 

  • U491
[1] Papadimitriou E, Yannis G, Golias J.A critical assessment of pedestrianbehavior models[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2009, 12(3): 242-255.
[2] Helbing D, Molnar P.Social force model for pedestrian dynamics[J]. Physical Review E, 1995, 51(5): 4282.
[3] Helbing D, Farkas I, Vicsek T.Simulating dynamical features of escape panic[J]. Nature, 2000, 407(6803): 487-490.
[4] Helbing D, Farkas I J, Molnar P, et al.Simulation of pedestrian crowds in normal and evacuation situations[J]. Pedestrian and Evacuation Dynamics, 2002, 21(2): 21-58.
[5] Helbing D, Buzna L, Johansson A, et al.Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions[J]. Transportation Science, 2005, 39(1): 1-24.
[6] Apel M.Simulation of pedestrian flows based on the social force model using theverlet link cell algorithm [D]. The Republic of Poland:Institute of Computing Science,Poznan University of Technology,2004.
[7] Johansson A.Pedestrian simulations with the social force model [D].Dresden, Germany: Institute for Transport & Economics, Dresden University of Technology, 2004.
[8] Moussaïd M, Helbing D, Garnier S, et al.Experimental study of the behavioural mechanisms underlying self-organization in human crowds[J]. Proceedings of the Royal Society of London B: Biological Sciences, 2009: 276(1668): 2755-2762.
[9] Zeng W, Chen P, Nakamura H, et al.Application of social force model to pedestrian behavior analysis at signalized crosswalk[J]. Transportation Research Part C: Emerging Technologies, 2014, 40: 143-159.
[10] Li M, Shi F, Chen D.Analyze bicycle-car mixed flow by social force model for collision risk evaluation[C]∥The 3rd International Conference on Road Safety and Simulation, Washington, DC,USA,2011:1-22.
[11] 江晟, 王殿海, 陈永恒, 等. 基于视频的行人运动轨迹再现与过街行为表达[J]. 东南大学学报: 自然科学版, 2012, 42(6): 1233-1237.
Jiang Sheng, Wang Dian-hai,Chen Yong-heng, et al.Pedestrian movement trajectory reappearance and crossing feature expression based on video processing[J]. Journal of Southeast University (Natural Science Edition), 2012, 42(6): 1233-1237.
[12] 江晟. 混合交通视频检测关键技术研究 [D]. 长春:吉林大学交通学院, 2013.
Jiang Sheng.Research on key technologies of mixed traffic video detection [D]. Changchun:College of Transportation, Jilin University, 2013.
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