A Hybrid Routing Algorithm for V2V Communication in VANETs Based on Blocked Q-Learning

DOI Web Site 参考文献30件
  • BI Xiang
    School of Computer Science and Information Engineering, Hefei University of Technology Postdoctoral Research Center, Wuhu Token Sciences Co., Ltd.
  • HUANG Huang
    School of Computer Science and Information Engineering, Hefei University of Technology
  • ZHANG Benhong
    School of Computer Science and Information Engineering, Hefei University of Technology Engineering Research Center of Safety Critical Industrial Measurement and Control Technology, Ministry of Education
  • WEI Xing
    School of Computer Science and Information Engineering, Hefei University of Technology Intelligent Manufacturing Institute, Hefei University of Technology

抄録

<p>It is of great significance to design a stable and reliable routing protocol for Vehicular Ad Hoc Networks (VANETs) that adopt Vehicle to Vehicle (V2V) communications in the face of frequent network topology changes. In this paper, we propose a hybrid routing algorithm, RCRIQ, based on improved Q-learning. For an established cluster structure, the cluster head is used to select the gateway vehicle according to the gateway utility function to expand the communication range of the cluster further. During the link construction stage, an improved Q-learning algorithm is adopted. The corresponding neighbor vehicle is chosen according to the maximum Q value in the neighbor list. The heuristic algorithm selects the next-hop by the maximum heuristic function value when selecting the next-hop neighbor node. The above two strategies are comprehensively evaluated to determine the next hop. This way ensures the optimal selection of the next hop in terms of reachability and other communication parameters. Simulation experiments show that the algorithm proposed in this article has better performance in terms of routing stability, throughput, and communication delay in the urban traffic scene.</p>

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