Method for identifying abnormal driving behavior

An automated driving assistance system, comprising:

• at least one processor;
• and
• a memory coupled to the at least one processor and storing programming instructions for execution by the at least one processor, wherein the programming instructions instruct the at least one processor to perform the following operations:
• automatically obtaining current vehicle driving behavior data of a vehicle as the vehicle is driving, the current vehicle driving behavior data including vehicle control parameters obtained from an electronic control unit or control system or a sensor of the vehicle;
• obtaining current vehicle driving scenario data;
• and
• determining, based on the current vehicle driving behavior data, whether the vehicle is in a state of suspicious abnormal driving behavior, and based on the vehicle being in the state of suspicious abnormal driving behavior, classifying the current vehicle driving scenario data, using a trained neural network, based on ambient environment information of the vehicle representing a driving scenario in which the vehicle is located to determine a current vehicle driving scenario, wherein the ambient environment information of the vehicle includes continuous parameters and discrete parameters and discretization processing is performed on the continuous parameters, determining from a plurality of predetermined algorithm logic types a specific algorithm logic that matches the current vehicle driving scenario of the vehicle and determining, based on at least the current vehicle driving behavior data and the specific algorithm logic, whether the suspicious abnormal driving behavior is abnormal driving behavior or normal driving behavior.

A computer program product comprising computer-executable instructions stored on a non-transitory computer-readable storage medium that, when executed by a processor, cause an apparatus to:

• automatically obtain current vehicle driving behavior data of a vehicle as the vehicle is driving, the current vehicle driving behavior data including vehicle control parameters obtained from an electronic control unit or control system or a sensor of the vehicle;
• determine, based on the current vehicle driving behavior data, whether a vehicle is in a state of suspicious abnormal driving behavior;
• obtain current vehicle driving scenario data based on the vehicle being in the state of suspicious abnormal driving behavior;
• classifying, using a trained neural network, the current vehicle driving scenario data based on ambient environment information of the vehicle representing a driving scenario in which the vehicle is located, wherein the ambient environment information of the vehicle includes continuous parameters and discrete parameters and discretization processing is performed on the continuous parameters, to determine a current vehicle driving scenario of the vehicle;
• determining from a plurality of predetermined algorithm logic types a specific algorithm logic that matches the current vehicle driving scenario of the vehicle;
• and
• determine, based on at least the current vehicle driving behavior data and the specific algorithm logic, whether the suspicious abnormal driving behavior is abnormal driving behavior or normal driving behavior.