道路交通网络节点分配优化策略研究进展

doi:10.16180/j.cnki.issn1007-7820.2023.03.013

Abstract

Abstract:

In order to further improve the traffic efficiency of urban road traffic network, a variety of intelligent optimization algorithms such as particle swarm optimization algorithm and neural network algorithm have attracted extensive attention. Recently, the popularization and application of deep learning technology has greatly improved the efficiency of node identification of urban traffic network, and the node scheduling of traffic network has expanded the application of deep learning technology. In this study, the key problems of traffic node scheduling are analyzed in detail, and the research status of relevant network node allocation is summarized. On this basis, the proposed study thoroughly discusses and analyzes the application prospect of node scheduling and deep learning in urban transportation network, and prospects the future research direction of node allocation optimization strategy in transportation network.

Key words: transportation network, node scheduling, deep learning, machine learning, vehicle networking, intelligent algorithm, heuristic search, collaborative control

CLC Number:

TN929.5

LU Dongxiang. Research Progress of Node Assignment Optimization Strategy in Road Traffic Network[J].Electronic Science and Technology, 2023, 36(3): 81-86.

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Research Progress of Node Assignment Optimization Strategy in Road Traffic Network

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