DOI: 10.11908/j.issn.0253-374x.20266

作者:

作者单位: 同济大学 道路与交通工程教育部重点实验室，上海 201800


作者简介: 柳本民（1968?），女，副教授，博士生导师，工学博士，主要研究方向为道路安全与环境。 E-mail：liubenming@tongji.edu.cn


通讯作者: 廖岩枫（1996?），女，硕士生，主要研究方向为道路安全与驾驶行为。E-mail：18217791871@163.com

中图分类号: U491


基金项目: 国家重点研发计划重点专项（2017YFC0803902）




Risk Prediction Model of Vehicle Driving in Small Radius Curves Based on Simulation Experiment
Author:

Affiliation: Key Laboratory of Road & Traffic Engineering of the Ministry of Education， Tongji University， Shanghai 201800， China


Fund Project:




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摘要:通过驾驶模拟实验对低等级公路车辆驾驶数据进行采集，从车辆过弯时的横向风险与纵向风险出发，对弯道的行驶数据进行统计分析，得到8个主要参数，并通过主成分分析筛选出速度标准差、切向加速度标准差及方向盘转速3个核心统计量，再以此为基础进行k均值聚类，分离出弱风险、急刹车、急转弯、强风险4类驾驶风险。最后取车辆过弯的前1/4时间窗口内的3个核心统计参数作为测试集，整条弯道的行驶数据作为训练集，通过Fisher进行建模，该模型的识别精度可达76.5%。



Abstract:The driving data of car driving in low-grade highway was collected from the simulation experiment. Focus on the horizontal risk versus vertical risk， 8 major statistics were calculated from the driving data， from which， 3 core statistics （standard deviation of velocity， tangential acceleration and steering wheel speed） were screened by principal component analysis（PCA）. Based on the 3 core statistics， 4 kinds of risks （weak risk， sharp brake， sharp turn， strong risk） were separated by k-mean clustering. Then， a risk prediction model of vehicle driving in small curves was founded based on Fisher， whose test set was the 3 core statistics of the initial 1/4 period that vehicle driving in curves， and training set was that of the whole curve. The accuracy of the risk prediction model was 76.5%.





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