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Comparison Between Cut-In Performance Model of ECE R157 and Behaviors of Chinese Drivers
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作者 Rui Liu Xuan Zhao +1 位作者 Xichan Zhu Jian Ma 《Automotive Innovation》 2025年第2期281-292,共12页
Unlike widely used ADAS test approaches based on predefined typical scenarios,a new ADAS test methodology has been proposed by the United Nations Economic Commission for Europe Regulation No.157(ECE R 157),which verif... Unlike widely used ADAS test approaches based on predefined typical scenarios,a new ADAS test methodology has been proposed by the United Nations Economic Commission for Europe Regulation No.157(ECE R 157),which verifies whether ADAS meet safety requirements by comparing them to driver performance models.However,whether the driver performance models in ECE R157 can be utilized to characterize driver behaviors in China has not been validated,which limits advancements of globally consistent ADAS test procedures.In order to compare human drivers with the cut-in performance model in ECE R157,51 cut-in cases from 65,000 km naturalistic driving data collected in China were applied to analyze response characteristics of following vehicle’s drivers in the cut-in scenario.The results can be summarized as follows.First of all,90%of the drivers release accelerators and 75%of the drivers brake before lane-changers reach lane lines,whereas the cut-in performance model in ECE R157 brakes about 0.95 s after lane-changers reach lane lines.This phenomenon can be explained by preview features of drivers.Secondly,some drivers release accelerators until they see clear lane-changing maneuvers,whereas some drivers anticipate possibilities of lane-changing very early and release accelerators in advance.Thirdly,time headway should be employed as a risk estimator in the cut-in scenario rather than time-to-collision.These results can help to calibrate parameters in the cut-in performance model of ECE R157 according to behaviors of Chinese drivers and increase the scope of application for the test methodology proposed in ECE R157. 展开更多
关键词 ECE r157 Intelligent vehicle test Safety validation Advanced driver assistance systems Cut-in scenario Driver model
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