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Real-time comprehensive driving ability evaluation algorithm for intelligent assisted driving

Green Energy and Intelligent Transportation 2023年第2期2卷 40-55页

作者： Fang Liu Feng Xue Wanru Wang Weixing Su Yang Liu Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems Tiangong UniversityTianjin 300387China BBT-E-6 Complete Vehicle BMW Brilliance Automotive Ltd.Shenyang Liaoning 110098China

To meet the needs of the human-machine co-driving decision problem in the intelligent assisted driving system for real-time comprehensive driving ability evaluation of drivers,this paper proposes a real-time comprehensive driving ability evaluation method that integrates driving skill,driving state,and driving ***,by analyzing the driving experiment data obtained based on the intelligent driving simulation platform(the experiment can effectively distinguish the driver's driving skills and avoid the interference of driving style),the feature values that significantly represent driving skills and driving state are selected,and the time correlation between driving state and driving skills is pointed ***,the concept of relativity in comprehensive driving ability evaluation is further *** this concept,the natural driving trajectory dataset-HighD is used to establish the distribution map of feature values of the human driver group as the evaluation benchmark to realize the relative evaluation of driving skill and driving ***,HighD is used to establish a distribution map of human driver style feature values as an evaluation benchmark to achieve relative driving style ***,a comprehensive driving ability evaluation model with a“punishment”and“affirmation”mechanism is *** experimental comparative analysis shows that the evaluation algorithm proposed in this paper can take into account the driver's driving skill,driving state,and driving style in the real-time comprehensive driving ability evaluation,and draw differential evaluation conclusions based on the“punishment”and“affirmation”mechanism model to achieve a comprehensive and objective evaluation of the driver's driving *** can meet the needs of human-machine shared driving decisions for driver's driving ability evaluation.

关键词： Driving ability evaluation Driving style unsupervised decision tree Gaussian kernel function Human-machine shared control

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