Road Traffic Accidents Model and Its Application Based on Driver's Self-Mistakes

To improve the traditional analysis method of driver accident, the paper analyzes the cases of road accidents and survey data from the microscopic aspect. An accident causes model is formulated to describe the driver' own mistake characteristics and its relation with the road traffic accidents. The weights of key influencing factors are determined by the improved AHP method and its influencing level is quantitatively analyzed. The improved AHP method reduces the impact of subjective factors on the analysis accuracy. Results show that drivers' error rate of perception is approaching 50.2%, the error rate of judgment is 38.9%, and the operational error rate accounts for only 10.9%. The main factors cause traffic accidents are drivers' low abilities to perceive and judge risk and accident. The results provide the scientific basis for the drivers' self-mistakes and accident prevention.

摘要为改进传统的驾驶员差错事故分析方法，探索机动车驾驶员差错事故致因分析的新途径。本文基于道路交通事故案例与调研数据资料，从微观角度分析机动车驾驶员自身差错事故，建立了驾驶员自身差错交通事故致因模型；运用改进的层次分析法确定了导致驾驶员自身差错事故发生的主要影响因素权重，减少了主观因素对分析精度的影响。结果表明，在机动车驾驶员自身差错交通事故中，驾驶员感知差错率占50.2%，判断决策差错率占38.9%，操作差错率仅占10.9%。机动车驾驶员感知和判断能力较差是导致交通事故发生的重要因素，研究结果可为机动车驾驶员事故预防与控制提供科学依据。