Automatic parking locus optimization method based on full-simultaneous dynamic optimization framework

Abstract

The invention discloses an automatic parking locus optimization method based on a full-simultaneous dynamic optimization framework, and brings forward a vehicle-environment integrated modeling dynamic optimization framework based on full-simultaneous solution strategy, for the purposes of solving the problem of safe parking at a narrow parking space within shortest time due to fast rhythm of cities, effectively eliminating influences exerted by different parking space shapes on locus planning strategies and optimizing a safe bump-free locus which has nonholonomic constraints and satisfies low-speed parking of vehicles within the shortest time. The method provided by the invention is crucially characterized in that vehicle-parking space obstacle avoidance integrated modeling is realized by use of an MPCC mathematic optimization technology, and at the same time, can optimize correlation indexes of vehicle kinetics and dynamics. According to the method, control information such as the speed, the front-wheel corner, the accelerated speed, the front-wheel angular velocity and the like of a vehicle tracking optimization locus can be directly obtained, and actual parking assistance is facilitated.

Description

technical field [0001] The invention relates to the key autonomous parking trajectory optimization technology in an unmanned driving system. Background technique [0002] This year, the technology of auto-parking system (APS) has developed rapidly. As an important part of the unmanned driving system, its purpose is to assist or replace the driver to complete the safe parking space of the vehicle. With the increase of vehicles and the shrinking of parking spaces, it is more difficult for drivers to park. Therefore, autonomous parking technology has developed rapidly. [0003] Scholars at home and abroad mainly use the following two methods to study autonomous parking: (1) The method based on fuzzy control: the parking experience of mature drivers is sorted into fuzzy rules, which are realized by controlling the steering angle of the car and the position of the relative parking space. parking. However, the control process lacks coherent planning, requires repeated adjustment...

AI Technical Summary

Problems solved by technology

However, the geometric method has its inherent limitations when dealing with autonomous parking problems: (1) The collision-free path obtained under the geometric method does not necessarily satisfy the kinematic and physical constraints of the car, so it is not necessarily feasible

(3) The geometric method can only obtain the shortest parking path, but cannot implement optimization under objective functions such as the shortest parking time and the least fuel consumption

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