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基于安全距离的元胞自动机交通流模型研究
引用本文:邱小平,于丹,孙若晓,杨达. 基于安全距离的元胞自动机交通流模型研究[J]. 交通运输系统工程与信息, 2015, 15(2): 54-60
作者姓名:邱小平  于丹  孙若晓  杨达
作者单位:1. 西南交通大学交通运输与物流学院,成都610031;2. 综合交通运输智能化国家地方联合工程实验室,成都610031; 3. 综合运输四川省重点实验室,成都610031
基金项目:国家自然科学基金( 51278429, 51408509);四川省科技厅项目(2013GZX0167, 2014ZR0091);中央高校基本业务经费(SWJTU11CX080);成都市科技局项目(2014-RK00-00072-ZF,2014-RK00-00056-ZF);国家973项目(2012CB725405).
摘    要:随着交通拥堵状况日益显著,整体交通安全性下降,交通事故率逐渐增大.基于提高驾驶安全性考虑,细化元胞长度,引入被广泛证明在描述车辆驾驶行为方面具有很高精度的Gipps 安全距离规则,对NaSch模型进行改进,提出一个新的基于安全距离的元胞自动机交通流模型.采用实测数据对模型进行标定和评估,进一步对模型进行数值模拟分析.模型评估结果显示,新建立的模型相对NaSch 模型精度更高.数值模拟结果表明,改进模型能够很好地表现交通流特性,再现实际交通中的自由流、同步流及拥堵流等交通现象.此外,还发现驾驶员对前车最大减速度估计过高时,会导致道路通行能力下降,而驾驶员对自身车辆最大减速度估计过高时,会在一定程度上增大道路的通行能力,但是很可能会造成不安全的驾驶行为,增加了事故率.

关 键 词:公路运输  安全距离  元胞自动机  驾驶行为  最大减速度  
收稿时间:2014-11-26

Cellular Automata Model Based on Safety Distance
QIU Xiao-ping,YU Dan,SUN Ruo-xiao,YANG Da. Cellular Automata Model Based on Safety Distance[J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(2): 54-60
Authors:QIU Xiao-ping  YU Dan  SUN Ruo-xiao  YANG Da
Affiliation:1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China; 2. Comprehensive Intelligent Transportation National and Local Joint Engineering Laboratory, Chengdu 610031, China; 3. Comprehensive Transportation Key Laboratory of Sichuan Province, Chengdu 610031, China
Abstract:With the traffic congestion increasing significantly, traffic safety level declines and traffic accident rate increases gradually. To improve driving safety, the length of the cellular cells is fined, and the Gipps’safe distance rule is introduced to improve the NaSch model, further, a new cellular automata traffic flow model is proposed. The Gipps’safe distance rule is widely proved to have good performance in describing the vehicle driving behavior. In addition, we use the field data to calibrate and evaluate the proposed model. The numerical simulation analysis is carried out to analyze the model. Model evaluation results show that the performance of the new model is better than NaSch model. The simulation results show that the improved model can describe the traffic flow characteristics well and can reproduce free flow, synchronized flow, congestion and other traffic phenomenon in the real traffic flow. Furthermore, the study also found that the drivers’overestimation of the maximum deceleration of vehicle ahead will lead to decreased road capacity. However, the drivers’overestimation of their own vehicle maximum deceleration will increase the capacity of the road, but is likely to cause unsafe driving behaviors and increase accident rate.
Keywords:highway transportation  safe distance  cellular automata  driving behavior  maximum deceleration
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