A multi-lane mixed traffic vehicle speed cooperative control method

By constructing hierarchical vehicle clusters and designing optimal controllers, and using the feedback gain matrix of CAVs to control HDVs, the problem of insufficient CAV cooperative leadership capability in multi-lane mixed traffic is solved, and efficient, safe and adaptive cooperative control of mixed traffic flow is achieved.

CN120564409BActive Publication Date: 2026-07-10SOUTHWEST UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SOUTHWEST UNIV
Filing Date
2025-05-20
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing technologies struggle to effectively utilize the collaborative leadership capabilities of connected autonomous vehicles (CAVs) in multi-lane mixed traffic scenarios to suppress the impact of adjacent lane disturbances on system stability, resulting in insufficient robustness of mixed traffic flow control strategies in complex scenarios.

Method used

By constructing a hierarchical vehicle cluster, with the CAV as the lead vehicle and the vehicles in adjacent lanes and behind the CAV as HDVs, a linearized state-space system model is built, an optimal controller is designed, and the feedback gain control quantity of the CAV is calculated through the feedback gain matrix to achieve compensatory control of the HDVs, dynamically adjusting the feedback gain of the CAV to suppress disturbances.

Benefits of technology

It enhances the multi-lane cooperative control capability, strengthens the system's dynamic controllability and adaptability, effectively suppresses disturbances in adjacent lanes, and achieves efficient, safe, and adaptive cooperative control of mixed traffic flow.

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Abstract

This invention belongs to the field of mixed traffic control technology, and particularly relates to a method for coordinated speed control of multi-lane mixed traffic vehicles, comprising: S1, constructing a vehicle cluster according to a preset form; S2, constructing a linearized state-space system model of the vehicle cluster and analyzing its state controllability; S3, designing the optimal controller for the vehicle vehicular activity (CAV); S4, acquiring the state data of the vehicle cluster and determining whether it meets the state controllability requirements. If it does, the CAV is controlled normally; if not, the corresponding feedback gain control quantity is calculated, and the feedback gain control quantity is used to control the speed of the CAV, guiding the speed and spacing of each HDV in the vehicle cluster, thereby stabilizing the vehicle cluster. This method can fully utilize the cooperative leadership capability of the CAV, effectively suppress the impact of adjacent lane disturbances on system stability, and achieve efficient, safe, and adaptive coordinated control of mixed traffic flow.
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