基于模糊逻辑的山区高速公路交通事故预测研究
Research on Prediction of Traffic Accidents on Mountainous Highways Based on Fuzzy Logic
吴云川 1李太峰 2田毕江 3熊昌安3
作者信息
- 1. 大理州公安局交通警察支队 大理 671000
- 2. 云南省综合交通发展中心 昆明 650031
- 3. 云南省交通规划设计研究院股份有限公司 云南数字交通重点实验室 昆明 650200
- 折叠
摘要
为解决事故预测中变量及变量关系之间的模糊性,引入模糊逻辑方法,建立基于模糊逻辑的山区高速公路交通事故预测模型.收集云南省某典型山区高速公路的道路几何线形和交通事故等数据,按道路是否位于山阴面进行分类,提出能表征特殊节点和不良天气影响程度的显著变量;将变量划分为 5 个模糊集合,并采用三角形、梯形隶属函数将变量模糊化,训练得到 693 条有效模糊控制规则,按照模糊推理机制对模型进行推理,反模糊化后得到精确的事故预测结果.结果表明,模型的预测精度、平均绝对误差和平均绝对百分比误差分别为 90.2,0.88 次/km,11%,预测精度较高且适用于同类型的山区高速公路.因此,利用模糊逻辑对山区高速进行事故预测具有一定的可行性和可移植性.
Abstract
To solve the fuzziness between variables and variable relationships in accident prediction,fuzzy logic is introduced to establish a fuzzy logic-based traffic accident prediction model for mountain-ous highways.The data of road geometric alignment and traffic accidents of a mountainous highway in Yunnan Province are collected,and the data are also classified according to whether the road is located on a shaded side of the mountain to propose significant variables that can characterize the degree of in-fluence of special nodes and bad weather.The variables are divided into five fuzzy sets,and triangular and trapezoidal affiliation functions are used to fuzzify the variables,and the variables are trained to obtain 693 effective fuzzy control rules.Then the model is reasoned according to the fuzzy inference mechanism,and the accurate accident prediction results are obtained after anti-fuzzification.The re-sults show that the prediction accuracy,average absolute error and average absolute percentage error of the model are 90.2%,0.88 times/km and 11%,respectively,and the prediction accuracy is high and applicable to the same type of mountain highway.Therefore,the use of fuzzy logic to predict acci-dents on mountainous highways has a certain degree of feasibility and portability.
关键词
交通安全/山区高速公路/交通事故预测/模糊逻辑/可移植性Key words
traffic safety/mountain highways/yraffic accident prediction/fuzzy logic/portability引用本文复制引用
基金项目
云南省交通运输厅科技创新及示范项目(2021-90-2)
国家重点研发计划项目(2022YFC3002601)
云南省数字交通重点实验室(202205AG070008)
云南省交通投资建设集团有限公司科技创新项目(YCIC-YF-2022-06)
出版年
2024
NETL
NSTL
万方数据