Research on the Optimal Deployment of Expressway Roadside Units under the Fusion Perception of Intelligent Connected Vehicles - Wang, Peng; Lu, Youfu; Chen, Ning; Zhang, Luyu; Kong, Weilin; Wang, Qingbin; Qin, Guizhi; Mou, Zhenhua (Applied sciences, 2023)
At present, there is still a lack of relevant theoretical guidance on the deployment of roadside RSU on expressways. In the face of the coexistence of V2V and V2I communication in the future, the deployment adjustment after the penetration of intelligent vehicles is not considered. Therefore, this paper proposes a roadside RSU deployment income model in consideration of the influence of V2V and V2I communication. Based on the optimal income of roadside RSU nodes, it achieves the optimization of the RSU deployment range and determines the optimal deployment spacing through the forwarding and relaying role of V2V communication so as to achieve cost savings. In terms of RSU coverage of positive income, it considers the impact of intelligent vehicles and reconstructs the traditional information flow–traffic flow coupling theory to innovatively realize the modeling of income within the information life cycle. In terms of the information transmission deficit, the WSN node energy loss model is reconstructed with permeability. Also, in terms of the construction and maintenance costs, the cost models are constructed for different cluster lengths. In order to provide a basis for expressway sensor network deployment, MATLAB software (version R2016B) is used to analyze the three-dimensional relationship between expressway traffic density, intelligent vehicle permeability, and roadside RSU deployment spacing as well as to determine the optimal roadside RSU deployment spacing with the income model. Finally, the model reliability is validated by the Warshell algorithm and the Kmeans clustering algorithm.