山区公路穿村镇路段过境车辆事故严重程度推理分析

为获取道路线形、驾驶员属性、车辆类型、事故形态等因素对山区公路穿村镇路段过境车辆事故严重程度的影响机制。本文基于元双公路(元谋—牟定)2012—2017年事故数据，利用社会网络分析法从人、车、路、环境等方面筛选出15个影响因素；基于机器学习方法构建贝叶斯网络模型；以事故严重程度为决策变量，分析不同证据变量与驾驶员行为共同作用的推理结果。结果表明：不安全驾驶行为与危险事故因素的共同作用，将会增加事故严重程度；当涉及货车时，由于未保持安全距离，伤人事故率增加8.2%；在弯坡组合路段，由于驾驶员判断失误，伤人事故率增加 19.6%；阴雨天行驶时，由于驾驶员判断失误，伤人事故率增加5.4%；由于操作不当，发生侧翻事故时，伤人事故概率增加3.1%。

Inferential Analysis of Vehicle Accident Severity in Mountainous Highway Crossing Villages

This paper investigates the impact of roadway alignment, driver attributes, vehicle types, accident patterns and other main factors on the severity of vehicle accidents on mountainous highway that cross villages and towns. Based on the 2012 to 2017 accident data of Yuanshuang Highway (Yuanmou-Mouding) in China, this paper identified 15 major factors from the aspects of human, vehicles, roads and environment using the social network analysis method. The Bayesian network model is developed based on machine learning method. Taking accident severity as decision variable, the study analyzes the reasoning results of the interaction between different evidence variables and driving behaviors. The results indicate that the combination of unsafe driving behavior and some risky factors would increase the severity of accidents. When trucks were involved, the accident rate with injury would increase by 8.2% if the safety distance is not satisfied. In the curve segment with slopes, the accident rate with injury would increase by 19.6% if the driver misjudges the driving conditions. The accident rate with injury would also increase by 5.4% on rainy days and the driver misjudges the driving conditions. The probability of injury would increase by 3.1% in the rollover accident caused by improper operation of the driver.