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Soft Computing

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03.04.2020 | Focus

Applying improved K-means algorithm into official service vehicle networking environment and research

verfasst von: Xiangxi Meng, Jianghua Lv, Shilong Ma

Erschienen in: Soft Computing | Ausgabe 11/2020

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Abstract

In order to improve the traffic efficiency of official vehicles in the traffic road network, a backpressure routing control strategy for multi-commodity flow (official traffic flow) using official vehicle network environmental data information is proposed. Firstly, the road network composed of official service vehicle-mounted wireless network nodes is used to collect information on road conditions and official service vehicles. In order to improve the real-time and forward-looking route control, an official service vehicle flow forecasting method is introduced to construct a virtual official service vehicle queue. A multi-commodity flow (official service vehicle flow) backpressure route method is proposed, and an official service vehicle control strategy is designed to improve the self-adaptive route of K-means algorithm. In addition, the weight of backpressure strategy is improved according to traffic pressure conditions, and the adaptability of backpressure route algorithm is improved by using optimized parameters. Finally, the simulation results show that the proposed method can effectively control traffic vehicles and improve traffic smoothness.

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Titel: Applying improved K-means algorithm into official service vehicle networking environment and research
verfasst von: Xiangxi Meng
Jianghua Lv
Shilong Ma
Publikationsdatum: 03.04.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 11/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-020-04893-w

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