基于车速比的城市交通事故交通影响程度评价

Evaluation of Traffic Influence Degree of Urban Traffic Accident Based on Speed Ratio

分析城市交通事故交通影响程度,对于评估交通应急等级及采取相应的应急对策具有重要的意义和现实价值。将城市交通事故对交通的影响与水波涟漪类比。基于事故发生前后道路车速的比值,借助水波原理,提出了交通影响系数的概念,并界定其作为评价交通影响程度的依据。针对某一给定类型的交通事故,在对35起交通事故调查数据进行筛选和整理的基础上,得到了交通影响系数时空分布图;采用变量控制法,利用MATLAB构建了交通影响系数与时间和距离的关系模型。针对不同事故特征的差异性,考虑事故发生后道路剩余通行能力的不同,采用城市道路车道利用系数计算得到了事故源修正系数。利用二重积分构建累积交通影响系数模型,计算出交通事故的综合交通影响程度值,从而评价交通事故对周边路网的综合交通影响。最后,假设某一交通事故,并对其进行VISSIM仿真分析,分别采用文中所构建的交通影响程度评价模型和根据实际仿真运行数据所建模型计算了该事故的综合交通影响程度值,两种方法计算的结果分别为0.666和0.648,误差在可接受的范围。结果表明:构建的交通影响程度评价模型是可行的。该研究成果可以在交通事故发生时给城市交通应急管理部门快速响应提供决策支持。

Analysis of traffic influence degree of urban traffic accident has important significance and realistic value for estimating traffic emergency grade and adopting corresponding emergency countermeasures. The influence of urban traffic accident on traffic is compared with the ripple of water. Based on the ratio of speeds before and after accident, the concept of traffic impact coefficient is proposed and defined as the basis for estimating traffic influence degree using water wave theory. Aiming at a certain given type of traffic accident, the time-space distribution chart of traffic impact coefficient is obtained based on data filtering and sorting of 35 traffic accidents. The relationship model among traffic impact coefficient, time and distance is established using MATLAB and variable control method. According to the variations of different traffic accident characteristics and considering the difference of remaining road capacity after the accident, the accident source modification factor is obtained by calculating the lane utilization factor of urban road. Using double integral, the accumulative traffic impact coefficient model is built to calculate the comprehensive traffic influence degree value, which is used to evaluate the comprehensive traffic impact of the accident on surrounding road network. Finally, based on VISSIM stimulation on an assumed accident, the comprehensive traffic influence degree value is computed by the traffic impact degree evaluation model established in the paper and the model built by the actual stimulation data respectively. The results of the 2 methods are 0. 666 and 0. 648 respectively. The error can be accepted, which shows that the established traffic impact evaluation model is feasible. The research result can provide decision-making support for traffic management department to quickly response in accident.