Lane changing decision-making method and device

Abstract

The invention discloses a lane changing decision-making method and device; based on the obtained first motion information of a own vehicle and the second motion information of environment vehicles, the driving environment of the own vehicle is divided into different areas; the relative directions of the environmental vehicles and the own vehicle in each area are the same; a target vehicle in eacharea is determined; a lane changing flag bit of each area is in a safe state or an unsafe state is determined based on the a relative distance and a relative speed between the target vehicle in each area and the own vehicle; and a target lane changing decision is made according to the lane changing flag bit of each area. The driving environment of the own vehicle is divided into different areas; whether the target vehicle generating potential threats to normal driving of the own vehicle exists in all the areas or not is determined, such that the final target lane changing decision is made; thewhole lane changing decision making process is simple and clear, and collection and training of a large amount of data are avoided.

Description

technical field [0001] The present invention relates to the technical field of automatic driving, and more specifically, relates to a lane-changing decision-making method and device. Background technique [0002] During the driving process, the vehicle usually performs lane changes autonomously in pursuit of faster speed and more free driving space. Compared with car-following behavior, lane-changing behavior needs to consider more complex surrounding vehicles and road environment information. In order for autonomous vehicles to have the lane-changing experience of human drivers and to be able to drive freely in the road environment, it is necessary to conduct in-depth research on lane-changing behavior. Reasonable lane-changing decision-making provides a good foundation for implementing lane-changing behavior, and is of great significance to ensure the safety and comfort of lane-changing. Currently, the most widely used autonomous lane-changing decision-making method is t...

AI Technical Summary

Problems solved by technology

[0004] Data-based algorithms require a large amount of data for model training and testing, and different drivers have very different lane-changing motivations under different working conditions, so it is difficult to collect comprehensive and complete lane-changing data

Moreover, the algorithm implementation process is cumbersome, and data processing, model selection, and model training all require a lot of resources in time and space, resulting in high cost for this lane-changing decision-making method.

In addition, data-based algorithms cannot use simple rules and formula relationships to represent input and output relationships, so the calculation process is opaque and cannot be explained

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