An intelligent vehicle lane changing decision method, apparatus, storage medium and an intelligent vehicle

Abstract

The embodiment of the application relates to an intelligent vehicle lane changing decision method, apparatus, storage medium and an intelligent vehicle. The intelligent vehicle lane changing decisionmethod includes the steps of determining information about the environment where an intelligent vehicle is currently traveling, wherein the environment information includes trajectory information andlane information; generating a first lane changing decision based on a first decision rule and the environment information; and generating second lane changing decision based on the first lane changing decision and a second decision rule. Based on the intelligent vehicle lane changing decision method, different lane changing decisions are coupled, and the decision rules between the different lanechanging decisions are decoupled, thereby reducing decision rules and avoiding decision efficiency degradation. Meanwhile, since different lane changing decisions deal with different lane changing requests, the rationality of intelligent vehicle lane changing can be raised.

Description

technical field [0001] The embodiment of the present application relates to the technical field of automatic driving, and specifically relates to a method, device, storage medium and smart car for making a lane change decision for a smart car. Background technique [0002] With the development of vehicle intelligent technology, intelligent vehicle automatic driving technology has gradually become a hot spot in the field of vehicle research. Smart cars need to face complex road environments during driving. How to make reasonable lane-changing decisions in complex and changeable environments has always been a difficult problem in the field of smart car technology. [0003] The existing lane-changing decision-making methods for intelligent vehicles can be roughly divided into two categories: rule-based lane-changing decision-making and learning-based lane-changing decision-making. Rule-based lane-changing decisions generally formulate lane-changing rules based on traffic rules...

AI Technical Summary

Problems solved by technology

This type of method has good stability and is easy to implement, but due to the need to consider various environmental factors, the number of rules formulated will become larger and larger, all states will be coupled together, and the finite state machine will become more and more bloated, which will lead to a decrease in decision-making efficiency; At the same time, due to the functional correlation or similarity between some lane-changing decisions, frequent lane-changing may occur

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