Safety impacts of red-light cameras at signalized intersections based on Cellular Automata models
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https://tandf.figshare.com/articles/dataset/Safety_impacts_of_red_light_cameras_at_signalized_intersections_based_on_Cellular_Automata_models/1102767/1
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ABSTRACTObjectiveThis study applies a simulation technique to evaluate the hypothesis that red-light cameras (RLCs) exert important effects on accident risks. Conflict occurrences are generated by simulation and compared at intersections with and without RLCs to assess the impact of RLCs on several conflict types under various traffic conditions.MethodConflict occurrences are generated through simulating vehicular interactions based on an improved Cellular Automata (CA) model. The CA model is calibrated and validated against field observations at approaches with and without RLCs. Simulation experiments are conducted for RLC and non-RLC intersections with different geometric layout and traffic demands to generate conflict occurrences which are analyzed to evaluate the hypothesis that RLCs exert important effects on road safety.ResultsThe comparison of simulated conflict occurrences show favorable safety impacts of RLCs on crossing conflicts, and unfavorable impacts for rear-end conflicts during red/amber phases. Corroborative results are found from broad analysis of accident occurrences.ConclusionsThe RLCs are found to impose mixed effect on accident risk at signalized intersections: crossing collisions are reduced while rear-end collisions may increase. The specially-developed CA model is found to be a feasible safety assessment tool.
摘要
研究目的:本研究采用仿真技术,旨在验证闯红灯摄像头(red-light cameras,RLCs)对事故风险存在显著影响这一假说。通过仿真生成冲突事件,并在设置与未设置RLCs的交叉口开展对比分析,以评估不同交通条件下RLCs对多类冲突类型的影响。
研究方法:本研究基于改进的元胞自动机(Cellular Automata,CA)模型模拟车辆交互行为以生成冲突事件。针对设置与未设置RLCs的交叉口现场观测数据,对该CA模型进行校准与验证。随后针对不同几何布局与交通需求的RLC交叉口及无RLC交叉口开展仿真实验,生成冲突事件并开展分析,以验证RLCs对道路安全存在显著影响的假说。
研究结果:仿真冲突事件的对比分析结果表明,RLCs对穿越冲突具有正向的安全改善效果,但在红灯/黄灯相位期间对追尾冲突存在不利影响。通过对事故事件的大范围分析,得到了一致性的验证结果。
研究结论:研究发现,RLCs对信号控制交叉口的事故风险存在混合影响:穿越碰撞事故有所减少,但追尾碰撞事故可能增加。此外,本研究自研的CA模型可作为一种可行的道路安全评估工具。
提供机构:
Taylor & Francis
创建时间:
2016-01-19



