A lane-changing decision-making method and system based on lane-changing interaction intention

Abstract

The invention discloses a lane-changing decision-making method and system based on lane-changing interaction intentions. The method includes: collecting lane-changing interaction data; labeling the lane-changing interaction data through road information and lane scenes, and extracting driving features from the lane-changing interaction data to construct a training set and a verification set; Lane intention; train the long-short-term memory network through the training set and the lateral lane-changing intention, and obtain the lateral lane-changing intention model; train the long-short-term memory network through the lateral lane-changing intention and driving characteristics, and obtain the longitudinal yielding intention model; according to the lateral lane-changing intention and longitudinal yield intention to determine the lane-changing interaction state of the lane-changing interactive vehicle; determine the lane-changing decision based on the lane-changing interaction state. By identifying the current lane-changing interaction intention of the vehicle, the present invention helps the self-driving vehicle make a correct decision when changing lanes in a lane-changing scene or when facing surrounding vehicles changing lanes, and improves traffic safety during the lane-changing process.

Description

technical field [0001] The present invention relates to the technical field of automatic driving, in particular to a lane-changing decision-making method and system based on lane-changing interaction intentions. Background technique [0002] With the increasing number of cars and the continuous improvement of the intelligence of autonomous vehicles, higher requirements are put forward for the understanding of vehicle-to-vehicle interaction behavior, and more and more attention has been paid to the research on vehicle-vehicle interaction behavior. Lane-changing behavior is a common basic driving scenario. The lane-changing model of autonomous driving vehicles has been extensively studied. However, the research on vehicle interaction in the process of lane-changing at home and abroad is not systematic enough. [0003] Improper driving operations such as illegal lane changes, cut-in and overtaking of vehicles may cause traffic conflicts and collisions, which greatly affect the ...

AI Technical Summary

Problems solved by technology

Lane-changing behavior is a common basic driving scenario. The lane-changing model of autonomous driving vehicles has been extensively studied. However, the research on vehicle interaction in the process of lane-changing at home and abroad is not yet systematic enough.

[0003] Improper driving operations such as illegal lane changes, cut-in, and overtaking of vehicles may cause traffic conflicts and collisions, which greatly affect the efficiency of traffic flow

In the lane-changing scene, it may be difficult for the current self-driving vehicles to make reasonable traffic decisions due to high traffic density and many uncertain factors, and it is impossible to reasonably interact with surrounding traffic participants.

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