A cooperative lane-changing decision method for intelligent networked vehicles in mixed traffic flow

Through communication between intelligent connected vehicles and following vehicles and driver personality classification, the difficult problem of lane changing decision-making of intelligent connected vehicles in mixed traffic flow is solved, safe and efficient lane changing behavior is achieved, and the safety and efficiency of road traffic are improved.

CN116758779BActive Publication Date: 2025-10-24SOUTHEAST UNIV
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Patent Information

Application Number
CN202310504994.X
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-05-06
Publication Date
2025-10-24
Estimated Expiration
2043-05-06

AI Technical Summary

Technical Problem

Existing research has failed to effectively address the decision-making approach of intelligent connected vehicles facing different types of following vehicles during lane changing in mixed traffic flows, especially considering the impact of human driver heterogeneity on lane changing behavior, resulting in insufficient road traffic safety and efficiency.

Method used

Through intelligent connected vehicles communicating with the following vehicle, collaborative or single-vehicle lane changing strategies are adopted according to the type of following vehicle. Combined with the driver's personality classification, the feasibility of lane changing behavior is determined, and environmental perception data and communication technology are used to make safe and smooth lane changing decisions.

Benefits of technology

It enables safe and efficient lane changing for intelligent connected vehicles in mixed traffic flows, reduces the impact on vehicles on main roads, and ensures the safety and stability of road traffic.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application discloses a cooperative lane-changing decision method for intelligent network-connected vehicles in mixed traffic flow, and relates to the field of intelligent traffic control. Effective data of surrounding vehicles within a sensing radius and effective data of road infrastructure are acquired. According to the type of the vehicle behind the target lane, the lane-changing behavior of the vehicle is judged. If the vehicle behind the target lane is an intelligent network-connected vehicle, a cooperative lane-changing strategy is adopted, the lane-changing feasibility is judged, a lane-changing request is sent to the vehicle behind the target lane and feedback is received, and different coordination protocols are adopted according to the time for the target vehicle to reach the end of the merging lane. If the vehicle behind the target lane is a human driver, a single-vehicle lane-changing strategy is adopted, and different lane-changing decisions are adopted according to the heterogeneity of the driver. The application comprehensively considers the possibility of intelligent network-connected vehicles in the lane-changing scene in the merging area in the mixed traffic flow environment, details different scenes of intelligent network-connected lane-changing, and further provides a decision basis for the lane-changing algorithm of the intelligent network-connected vehicle, and provides a guarantee for future traffic safety and efficiency.
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