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Research on Adaptive Vehicle Road Cooperation Message Transmission Method Based on Ant Colony Algorithm
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Mingjian Liu1, 2, Sijia Zhang1, 2, Hua Sun1
Automobile Technology | 2023, (3) : 35 - 41
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Automobile Technology | 2023, (3): 35-41
Research on Adaptive Vehicle Road Cooperation Message Transmission Method Based on Ant Colony Algorithm
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Mingjian Liu1, 2, Sijia Zhang1, 2, Hua Sun1
Affiliations
  • 1 Dalian Ocean University, Dalian 1160232
  • 2 Key Laboratory of Environment Controlled Aquaculture, Ministry of Education, Dalian Ocean University, Dalian 116023
Published: 2023-03-24 doi: 10.19620/j.cnki.1000-3703.20220440
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In order to effectively solve the problem of limited amount of downloaded data due to the short travel time of vehicles in the coverage of Road Side Unit (RSU) during high-speed movement, this paper proposed a message transmission strategy of vehicle road cooperation mode based on ant colony algorithm. According to the characteristics that information such as vehicle data can be shared between RSUs, the corresponding heuristic function and the corresponding path pheromone update principle were designed to form multiple vehicle road cooperation communication groups, which increased the amount and types of data transmission in the network and avoid falling into the local optimal solution. SUMO simulation platform was utilized for experimental verification. The results show that, compared with the non-cooperation, Coalition Formation Games (CGS) and Multilevel Hyper-graph Partitioning Based on Heavy Edge Matching Scheme (MHEMs), the proposed strategy is better than the above strategies in terms of information transmission volume, road network revenue and operating time, which proves the effectiveness of this strategy.

VANET  /  Road Side Unit (RSU)  /  Cooperative communication  /  Ant colony algorithm  /  Relay selection
Mingjian Liu, Sijia Zhang, Hua Sun. Research on Adaptive Vehicle Road Cooperation Message Transmission Method Based on Ant Colony Algorithm[J]. Automobile Technology, 2023 , (3) : 35 -41 . DOI: 10.19620/j.cnki.1000-3703.20220440
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doi: 10.19620/j.cnki.1000-3703.20220440
  • Online Date：2025-12-07
  • Published：2023-03-24
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  • Revised：2022-07-02
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    1 Dalian Ocean University, Dalian 1160232
    2 Key Laboratory of Environment Controlled Aquaculture, Ministry of Education, Dalian Ocean University, Dalian 116023
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