Centre for Infrastructure Systems, Nanyang Technological University, 40 Nanyang Avenue, 639798, Singapore.
Accid Anal Prev. 2014 Feb;63:94-103. doi: 10.1016/j.aap.2013.10.023. Epub 2013 Nov 6.
At intersection, vehicles coming from different directions conflict with each other. Improper geometric design and signal settings at signalized intersection will increase occurrence of conflicts between road users and results in a reduction of the safety level. This study established a cellular automata (CA) model to simulate vehicular interactions involving right-turn vehicles (as similar to left-turn vehicles in US). Through various simulation scenarios for four case cross-intersections, the relationships between conflict occurrences involving right-turn vehicles with traffic volume and right-turn movement control strategies are analyzed. Impacts of traffic volume, permissive right-turn compared to red-amber-green (RAG) arrow, shared straight-through and right-turn lane as well as signal setting are estimated from simulation results. The simulation model is found to be able to provide reasonable assessment of conflicts through comparison of existed simulation approach and observed accidents. Through the proposed approach, prediction models for occurrences and severity of vehicle conflicts can be developed for various geometric layouts and traffic control strategies.
在交叉口,来自不同方向的车辆相互冲突。信号交叉口的不当几何设计和信号设置会增加道路使用者之间冲突的发生,从而降低安全水平。本研究建立了元胞自动机(CA)模型来模拟涉及右转车辆的车辆交互(类似于美国的左转车辆)。通过对四个案例交叉路口的各种模拟场景,分析了涉及右转车辆的冲突发生与交通量以及右转运动控制策略之间的关系。从模拟结果估计了交通量、与 RAG 箭头相比的允许右转、共享直行车道和右转车道以及信号设置的影响。通过将现有的模拟方法与观察到的事故进行比较,发现该模拟模型能够通过合理评估冲突。通过所提出的方法,可以为各种几何布局和交通控制策略开发车辆冲突发生和严重程度的预测模型。