广西师范大学学报（自然科学版） ›› 2017, Vol. 35 ›› Issue (3): 14-21.doi: 10.16088/j.issn.1001-6600.2017.03.002

• • 上一篇    下一篇

连续记忆效应的交通流跟驰建模与稳定性分析

陈春燕, 许志鹏, 邝华*   

  1. 广西师范大学物理科学与技术学院,广西桂林541004
  • 出版日期:2017-07-25 发布日期:2018-07-25
  • 通讯作者: 邝华(1978—),男,广西桂林人,广西师范大学教授,博士。E-mail: khphy@gxnu.edu.cn
  • 基金资助:
    国家自然科学基金(11262005);广西自然科学基金(2014GXNSFAA118007);广西高校科研一般项目(YB2014034);广西研究生教育创新计划(YCSW2017096,YCSZ2016039)

Modeling and Stability Analysis of Traffic Flow Car-following Modelwith Continuous Memory Effect

CHEN Chunyan, XU Zhipeng, KUANG Hua*   

  1. College of Physical Science and Technology, Guangxi Normal University, Guilin Guangxi 541004, China
  • Online:2017-07-25 Published:2018-07-25

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摘要： 为了研究驾驶员的自主特性对交通流的影响,考虑实际交通中驾驶员对车速变化的连续记忆效应,本文提出一个改进的自稳定控制驾驶跟驰模型,以期提高交通流的稳定性。通过线性稳定性分析,得到新模型的稳定性条件为a>2V′(b)(1-λγ);与Bando的优化速度(optimal velocity,OV)模型相比,自由流稳定的敏感系数临界值ac变小,稳定区域明显增加。数值模拟结果表明,驾驶员的连续记忆效应能够显著地提高车流的稳定性,并有效地抑制交通流堵塞。

关键词: 交通流, 跟驰模型, 稳定性分析, 数值模拟

Abstract: In order to investigate the impacts of driver’s self-determination characteristic on traffic flow, an extended self-stabilizing control driving car-following model is proposed by considering the driver’s continuous memory for vehicle velocity changes in real traffic. It is expected that the stability of traffic flow can be improved. The stability condition a>2V′(b)(1-λγ) of this model is obtained by using the linear stability analysis. Compared with the Bando’s optimal velocity (OV) model, it can be found that the critical value ac of the sensitivity in the new model decreases and the stable region is apparently enlarged. The numerical simulation results show that the effect of driver’s continuous memory can obviously improve the stability of traffic flow, and effectively suppress the traffic jams.

Key words: traffic flow, car-following model, stability analysis, numerical simulation

中图分类号: 

  • U491.1
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