Abstract: The application discloses an optical cable assembly and an optical cable testing method. The optical cable assembly comprises: an optical cable wire with a test end; a spool for winding the optical cable; a connection assembly has an optical cable connection port and a test port, the connection assembly is configured to connect objects at both ends of the connection assembly, and the test end of the optical cable is connected to the connection assembly as an object at one end of the optical cable connection port, the test port is located at an operable area of the spool, configured to connect the test equipment to form an optical path between the test equipment and the optical cable wire when the optical cable is tested.

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.