交通信息与安全2024，Vol.42Issue(6)：55-63,73,10.DOI:10.3963/j.jssn.1674-4861.2024.06.006
基于多重客观指标表征的驾驶人接管绩效评估方法
An Evaluation Model for Driver Takeover Performance Based on Multi-objective Indicators Representation
摘要
Abstract
The takeover performance of drivers is of great significance for the safety,driving experience,and accep-tance of conditionally automated vehicles.To study the impacts of driver behavior on takeover performance,a com-prehensive evaluation representation index,takeover performance level(TOPL),is proposed,and a model based on an improved EWM-TOPSIS method is constructed to evaluate TOPL.The model determines the objective weight of each index using the entropy weight method(EWM),and then codes and maps each index based on the positive and negative ideal solutions in the technique for order preference by similarity to ideal solution(TOPSIS)model,thereby constructing the TOPL evaluation model.To verify the effectiveness of the model,46 drivers participated in a hu-man-machine co-driving takeover experiment,from which multidimensional evaluation indicators representing the safety,comfort,and smoothness of driver takeover performance are extracted.The study examines non-driving-relat-ed tasks by drivers during takeover and the impacts of the lead time for takeover requests on the level of driver take-over performance.Furthermore,the study analyzed the significant impacts of driver age and standard non-driving-re-lated task performance on TOPL.The results show that both driver age and non-driving-related task performance scores significantly impact TOPL.Additionally,significant differences in driver mileage are observed between the mileage ranges of 50000 to 100000 km,0 to 50000 km,and 100000 to 1000000 km.A significant negative correla-tion exists among the maximum yaw rate,maximum lateral acceleration,maximum lateral velocity,throttle depth standard deviation,and TOPL,whereas the time to reach the takeover boundary is significantly positively correlated with TOPL.In relation to varying takeover time budgets and the performance in completing non-driving tasks,TOPL exhibited the minimum takeover time budget of 4 s,and its takeover performance level is observed to be lower under conditions of emergency takeover.Additionally,when the driver's score in non-driving task completion fell below 60,TOPL recorded the highest values,and the TOPL decreases as the score increases.关键词
智能交通/接管绩效水平/EWM-TOPSIS法/人机接管/眼动数据/车辆动力学Key words
intelligent transportation/takeover Performance Level/Entropy Weight Method/Human-machine take-over/eye-tracking data/vehicle dynamics分类
交通工程引用本文复制引用
王丹,朱曰莹,张策,林业..基于多重客观指标表征的驾驶人接管绩效评估方法[J].交通信息与安全,2024,42(6):55-63,73,10.基金项目
国家自然科学基金项目(52072259、51505332)资助 （52072259、51505332）
