A unified automatic driving horizontal planning method and system

Abstract

A unified horizontal planning method for automatic driving, including: uniformly describing the surrounding environment information of the vehicle; based on the uniformly described surrounding environment information of the vehicle, planning an executable trajectory in real time while the vehicle is driving; executing the executable trajectory and guiding The vehicle runs laterally; through the above three steps, optimal local trajectory planning based on various constraints, performance indicators and driving behavior is achieved. A unified horizontal planning system for autonomous driving, including three sub-modules: environment model, planning algorithm and vehicle control. The environment model sub-module builds a unified local environment model based on environmental perception information, traffic rules and the nature of traffic participants, and uniformly describes the environment information around the vehicle to reflect the potential danger level around the vehicle; the planning algorithm sub-module considers the vehicle Non-holonomic constraints, safety and comfort requirements, and based on the environment model, plan executable trajectories in real time during vehicle driving.

Description

technical field [0001] The invention belongs to the technical field of automobiles and relates to an automobile automatic driving system, in particular to a horizontal planning technology of the automobile automatic driving system. Background technique [0002] Smart car technology has great potential in terms of travel safety, energy saving and environmental protection, and is considered to be an effective way to solve traffic congestion, reduce traffic accidents and improve environmental pollution. In the recent period, self-driving car technology has received widespread attention and has become one of the main directions of future car development. [0003] Generally speaking, an automatic driving system includes the following modules: environmental perception module, motion planning module, control execution module and human-machine interface module. The above four modules are crucial to the entire automatic driving system and directly affect the intelligence of the syste...

AI Technical Summary

Problems solved by technology

At present, there are many researches on lateral motion planning for autonomous driving at home and abroad, including traditional artificial potential field method, grid-based search method, sampling search method and discrete optimal method, etc. The above schemes have their own advantages, but there are still shortcomings. There is an urgent need for further improvement

Images