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Applying improved K-means algorithm into official service vehicle networking environment and research.
- Source :
-
Soft Computing - A Fusion of Foundations, Methodologies & Applications . Jun2020, Vol. 24 Issue 11, p8355-8363. 9p. - Publication Year :
- 2020
-
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. [ABSTRACT FROM AUTHOR]
- Subjects :
- *K-means clustering
*TRAFFIC flow
*TRAFFIC engineering
*VEHICLES
Subjects
Details
- Language :
- English
- ISSN :
- 14327643
- Volume :
- 24
- Issue :
- 11
- Database :
- Academic Search Index
- Journal :
- Soft Computing - A Fusion of Foundations, Methodologies & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 143057002
- Full Text :
- https://doi.org/10.1007/s00500-020-04893-w