Multi-intersection inter-cluster coupling-time attention multi-target robust co-regulation method

CN121921981BActive Publication Date: 2026-07-21ZHONGBEI UNIV
View PDF 2 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHONGBEI UNIV
Filing Date
2026-01-26
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing traffic signal control methods fail to fully consider the mutual influence and constraints of traffic flow at multiple intersections in urban road networks. This makes it difficult for the optimization effect of a single intersection to radiate globally, the control effect is easily affected by interference, and the feedback correction mechanism is insufficient, failing to meet the global coordinated control needs of complex road networks.

Method used

A robust collaborative control method with multi-intersection cluster coupling and temporal attention is adopted. Multi-dimensional traffic data is collected through sensor networks, and generative adversarial networks are used for data augmentation. The method combines density peak-adaptive K-value clustering algorithm and improved multi-objective robust particle swarm optimization algorithm to calculate the comprehensive priority weight of intersections and adjust the traffic light timing scheme to achieve dynamic adaptation and anti-interference capability.

Benefits of technology

It improves the overall coordination and dynamic adaptability of traffic signal control at multiple intersections, enhances the efficiency of control resource allocation, significantly reduces the risk of control failure under emergencies, and improves traffic operation efficiency and stability.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN121921981B_ABST
    Figure CN121921981B_ABST
Patent Text Reader

Abstract

The present application belongs to the field of intelligent traffic control, and particularly relates to a multi-intersection cluster coupling-time sequence attention multi-objective robust collaborative control method, aiming to improve the global coordination of multi-intersection traffic signal control. It comprises S1, collecting multi-dimensional traffic related data of multiple intersections through a sensor network, and after preprocessing and generation of a generative adversarial network to achieve missing data enhancement and completion, obtaining a standardized enhanced data set; S2, using a density peak value-adaptive K value clustering algorithm to process the standardized enhanced data set, obtaining data clusters, core intersections within each cluster, and key inter-cluster intersections; S3, based on the related data of the core intersections and the key inter-cluster intersections, calculating the comprehensive priority weight of each intersection through a cluster coupling-time sequence attention weight model; S4, combining the comprehensive priority weight, using an improved multi-objective robust particle swarm optimization algorithm, constructing a multi-objective robust optimization function and introducing a constraint condition, and adjusting the timing scheme of each intersection traffic signal.
Need to check novelty before this filing date? Find Prior Art