Trajectory tracking control method for autonomous vehicles

Abstract

A self-driving car trajectory tracking control method. In the process of modeling the trajectory tracking control of self-driving cars, the inevitable network delay and data packet loss problems are taken into account, and the generalized delay expression is more conducive to the controller. the design of. The design of trajectory tracking control for autonomous vehicles comprehensively considers the uncertainty of the vehicle dynamics model and the influence of external disturbances, improving the vehicle's handling stability and the robustness of trajectory tracking control. By solving linear matrix inequalities, the problem of trajectory tracking and control of autonomous vehicles involving network delay and data packet loss is solved, which is easy to calculate. By solving the convex optimization problem, the lower bound of the disturbance suppression performance index of the autonomous vehicle trajectory tracking control problem can be calculated, and thus the optimal trajectory tracking controller can be obtained.

Description

technical field [0001] The invention relates to the field of trajectory tracking control of an automatic driving vehicle, in particular to a method for controlling the trajectory of an automatic driving vehicle. Background technique [0002] Self-driving cars can effectively improve the driving safety of vehicles, achieve better road utilization, and greatly reduce the cost of mobility, which provides the possibility to fundamentally change the traditional mode of transportation. Therefore, it has become an emerging research hotspot in recent years. . As one of the key technologies of autonomous vehicles, the vehicle's trajectory tracking control goal is how to control the vehicle's steering system so that the vehicle can drive along the desired route while ensuring the vehicle's driving safety and ride comfort. The tracking deviation generated during the driving process of the self-driving car, that is, the distance deviation and the angle deviation, and the trajectory tra...

AI Technical Summary

Problems solved by technology

[0003] The existing trajectory tracking control algorithms for autonomous vehicles include fuzzy control, adaptive robust control, iterative learning control, sliding mode control, model predictive control methods, etc., and most of these control methods are based on precise mathematical models. The driving conditions of the vehicle are complex and changeable, and the actual vehicle dynamics model has a high degree of uncertainty and is easily affected by external disturbances

At the same time, there are usually unavoidable delays and data packet loss problems in the process of vehicle state measurement and signal transmission, which will greatly reduce the performance of the controller and even destroy the stability of the system

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