基于追尾危险感知模糊推理的交通流运行安全评价

Safety Evaluation of Traffic Flow Operation Based on Fuzzy Inference of Risk Perception of Rear-end Collision

为了有效替代基于事故数据的传统追尾风险评价方法,对微观驾驶员追尾危险感知模糊推理中的跟驰安全距离计算方法,包括影响驾驶员反应时间的天气状况隶属度函数进行了改进.以此为基础,提出可评价整个行车环境安全的道路行车危险总体感知度指标;构建了一个衡量宏观交通流的平均追尾风险评价指标,并通过Aimsun仿真软件得到不同交通条件下的平均追尾风险评价指标值,采用通过模糊聚类方法对该指标进行等级划分,可为道路交通事故预警技术提供支持.

In order to effectively surrogate the traditional evaluation method based on the accident data,the calculation method of car-following safety distance including the membership function of weather condition in the microscopic fuzzy inference system for risk perception was improved.The whole road risk perception index was put forward to measure the total driving environment and the average risk evaluation indicator of rear-end collision was developed for macroscopic traffic flow.The value of the average risk indicator could be achieved by simulation of AIMSUN software.Then,the Fuzzy c-means cluster method was used to develop the criterion of the indicator.Therefore,the research results can provide a support for the early warning technology of traffic accidents.