Traffic congestion recognition based on information entropy

Chenxing Guo; Juan Zhang; Zhen Cao

doi:10.1117/12.2613915

10 November 2021 Traffic congestion recognition based on information entropy

Chenxing Guo, Juan Zhang, Zhen Cao

Proceedings Volume 12050, International Conference on Smart Transportation and City Engineering 2021; 1205021 (2021) https://doi.org/10.1117/12.2613915
Event: 2021 International Conference on Smart Transportation and City Engineering, 2021, Chongqing, China

Abstract

Urban road traffic key nodes have a great influence on the urban road traffic, traffic state key nodes will also affect the adjacent nodes, thus a greater influence on road network, the information entropy can characterize degree of chaos system, this article through to acquisition of various lane traffic tunnel section, the information entropy to calculate the key nodes, Then, node information entropy is used to represent the degree of traffic congestion in urban tunnel sections. Finally, statistical analysis is conducted to find the change law of information entropy at the intersection entry point and the entrance information entropy at the tunnel exit.

Citation Download Citation

Chenxing Guo, Juan Zhang, and Zhen Cao "Traffic congestion recognition based on information entropy", Proc. SPIE 12050, International Conference on Smart Transportation and City Engineering 2021, 1205021 (10 November 2021); https://doi.org/10.1117/12.2613915

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