Wang Junhua, Kong Yumeng, Fu Ting, Stipancic Joshua
College of Transportation Engineering, Tongji University, Shanghai, China.
Department of Civil Engineering and Applied Mechanics, McGill University, Montreal, Canada.
PLoS One. 2017 Sep 8;12(9):e0184564. doi: 10.1371/journal.pone.0184564. eCollection 2017.
This paper presents the use of the Aimsun microsimulation program to simulate vehicle violating behaviors and observe their impact on road traffic crash risk. Plugins for violations of speeding, slow driving, and abrupt stopping were developed using Aimsun's API and SDK module. A safety analysis plugin for investigating probability of rear-end collisions was developed, and a method for analyzing collision risk is proposed. A Fuzzy C-mean Clustering algorithm was developed to identify high risk states in different road segments over time. Results of a simulation experiment based on the G15 Expressway in Shanghai showed that abrupt stopping had the greatest impact on increasing collision risk, and the impact of violations increased with traffic volume. The methodology allows for the evaluation and monitoring of risks, alerting of road hazards, and identification of hotspots, and could be applied to the operations of existing facilities or planning of future ones.
本文介绍了使用Aimsun微观模拟程序来模拟车辆违规行为,并观察其对道路交通事故风险的影响。利用Aimsun的应用程序编程接口(API)和软件开发工具包(SDK)模块开发了超速、慢速行驶和急停违规行为的插件。开发了用于调查追尾碰撞概率的安全分析插件,并提出了一种分析碰撞风险的方法。开发了一种模糊C均值聚类算法,以识别不同路段随时间变化的高风险状态。基于上海G15高速公路的模拟实验结果表明,急停对增加碰撞风险的影响最大,且违规行为的影响随交通量增加而增大。该方法可用于风险评估与监测、道路危险预警以及热点识别,并可应用于现有设施的运营或未来设施的规划。