深圳大学学报（理工版）2025，Vol.42Issue(1)：94-104,11.DOI:10.3724/SP.J.1249.2025.01094
基于HighD数据集的高速公路小客车换道风险分析
Lane-changing risk analysis of passenger cars on highways based on the HighD dataset
摘要
Abstract
To investigate the microscopic lane-changing behavior characteristics and associated risk for passenger cars on highways,we extracted lane-changing trajectories of the subject vehicle and driving data of surrounding vehicles from the HighD dataset.The focus is on the analyzing the subject vehicle's lane-changing behavioral patterns when there are vehicles ahead and behind in the target lane.Based on the lane-change conflict characteristics of light-duty vehicles on highways,we extracted lane-change risk indicators and established models for accident risk rates based on stopping distance coefficients and accident severity based on speed differences.Fault tree analysis was employed to calculate the lane-change risk index and evaluate lane-change safety.Additionally,the lane-change risk was classified into four levels using the k-means clustering algorithm.We established a lane-changing risk prediction model based on the gradient boosted tree(GBDT)framework to predict and validate the lane-changing risk for passenger car drivers using different feature combinations.The results show that the lane change risk prediction model with selected velocity-acceleration hybrid features provides the best prediction performance,contributing to improved lane-changing safety warnings for highway passenger cars.The findings can provide references for understanding the lane-changing behavior characteristics of passenger cars on highways,driving behavior pattern recognition and the parameter settings of driver assistance systems.关键词
交通工程/换道轨迹/换道风险/故障树分析/k-means聚类/梯度提升决策树Key words
traffic engineering/lane-changing trajectory/lane-changing risk/fault-tree analysis/k-means clustering/gradient boosting decision tree(GBDT)分类
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刘通,杨波,杨雪琦,刘唐志,刘星良,吴攀..基于HighD数据集的高速公路小客车换道风险分析[J].深圳大学学报（理工版）,2025,42(1):94-104,11.基金项目
National Natural Science Foundation of China(52172341,52402419) （52172341,52402419）
Natural Science Foundation of Chongqing(CSTB2022NSCQ-MSX0519) （CSTB2022NSCQ-MSX0519）
Talent Plan Technology Innovation and Application Development Project of Chongqing(CQYC2020030283) 国家自然科学基金资助项目(52172341,52402419) （CQYC2020030283）
重庆市自然科学基金资助项目(CSTB2022NSCQ-MSX0519) （CSTB2022NSCQ-MSX0519）
重庆市英才计划技术创新与应用发展基金资助项目(CQYC2020030283) （CQYC2020030283）
