Abstract: The present disclosure relates to an evaluation method and system for steering comfort in a human machine cooperative take-over control process of an autonomous vehicle, and a storage medium, thereby avoiding a defect that most comfort evaluation methods are applicable only in laboratory conditions, and also solving a problem that most comfort evaluation methods do not consider non-traditional control characteristics of a driver in a take-over control process. The method of the present disclosure includes: acquiring vehicle data information in a current driving cycle, and preprocessing the vehicle data information to form preprocessed vehicle data information; and using the preprocessed vehicle data information as an input to a well-trained comfort model library, and performing log probability matching calculation on the basis of the comfort model library, to form a comfort recognition result corresponding to comfort.

Abstract: The present disclosure relates to an evaluation method and system for steering comfort in a human machine cooperative take-over control process of an autonomous vehicle, and a storage medium, thereby avoiding a defect that most comfort evaluation methods are applicable only in laboratory conditions, and also solving a problem that most comfort evaluation methods do not consider non-traditional control characteristics of a driver in a take-over control process. The method of the present disclosure includes: acquiring vehicle data information in a current driving cycle, and preprocessing the vehicle data information to form preprocessed vehicle data information; and using the preprocessed vehicle data information as an input to a well-trained comfort model library, and performing log probability matching calculation on the basis of the comfort model library, to form a comfort recognition result corresponding to comfort.