Vehicle data processing method, autonomous vehicle, and computer-readable storage medium

An autonomous vehicle, comprising:

• a processor;
• a memory coupled to the processor;
• and
• one or more computer programs stored in the memory and executable on the processor;
• wherein, the one or more computer programs comprise:
• instructions for obtaining a yaw rate and a vehicle sideslip angle of the vehicle during driving, and constructing a phase plane diagram configured to characterize lateral vehicle dynamics state based on the yaw rate and the vehicle sideslip angle;
• instructions for identifying a first region in the phase plane diagram by performing dynamic stability analysis of the vehicle on the phase plane diagram, wherein the first region is a region where the vehicle can travel stably along a preset trajectory;
• instructions for predicting lateral stability constraint information of the vehicle state within a preset horizon based on boundary characteristics of the first region;
• instructions for designing a cost function of a model predictive controller of the vehicle, and obtaining a first control quantity through receding horizon control based on the lateral stability constraint information and the cost function;
• and
• instructions for obtaining a feedback compensation control quantity of the vehicle, obtaining a second control quantity based on the first control quantity and the feedback compensation control quantity, and controlling the vehicle to perform closed-loop trajectory tracking based on the second control quantity and a reference trajectory, wherein the second control quantity is a composite control quantity.

A non-transitory computer-readable storage medium for storing computer-executable instructions or one or more computer programs, wherein the computer-executable instructions or the one or more computer programs, when executed by a processor, implement a vehicle data processing method comprising:

• obtaining a yaw rate and a vehicle sideslip angle of the vehicle during driving, and constructing a phase plane diagram configured to characterize lateral vehicle dynamics state based on the yaw rate and the vehicle sideslip angle;
• identifying a first region in the phase plane diagram by performing dynamic stability analysis of the vehicle on the phase plane diagram, wherein the first region is a region where the vehicle can travel stably along a preset trajectory;
• predicting lateral stability constraint information of the vehicle state within a preset horizon based on boundary characteristics of the first region;
• designing a cost function of a model predictive controller of the vehicle, and obtaining a first control quantity through receding horizon control based on the lateral stability constraint information and the cost function;
• and
• obtaining a feedback compensation control quantity of the vehicle, obtaining a second control quantity based on the first control quantity and the feedback compensation control quantity, and controlling the vehicle to perform closed-loop trajectory tracking based on the second control quantity and a reference trajectory, wherein the second control quantity is a composite control quantity.