Roadside infrastructure deployment scheme based on Internet of Vehicles information service demand

Abstract

Roadside unit (RSU) plays an important role in communication relay and data processing in the Internet of Vehicles. The rational deployment of roadside units directly affects the operational efficiency and system robustness of the Internet of Vehicles. This article proposes an RSU deployment scheme based on vehicular transmission demand. First, the mobility model of vehicles is mined through system communication transmission requirements to determine the total delay of vehicle communication transmission tasks. The delay includes two parts, namely, the vehicle data transmission delay and the channel service delay. Second, the optimization objective of the model is established, and some parameters such as inhibition distance coefficient are defined as constraint conditions. Finally, a evolutionary feature‐based RSU deployment algorithm, ICA‐EFRDA, preprocessed by a greedy algorithm is proposed to implement RSU deployment. The deployment results show that the proposed scheme has lower delay and higher coverage time ratio than the EFRDA scheme in both urban and suburban road networks. Under limited cost constraints, the system decides to place a limited number of RSUs in low‐traffic density areas of the suburban road network to improve performance. When the traffic density is high, the increased placement of RSUs in the urban road network has a more obvious effect on improving the service capability of the system. Under different deployment cost constraints, ICA‐EFRDA outperforms the comparison schemes in terms of the contacts per trip, contact probability, and packet delivery ratio.

Optimization of Roadside Unit Deployment on Highways under the Evolution of Intelligent Connected-Vehicle Permeability

“…Ni Y. et al [26] proposed the Unified RSU Deployment Algorithm (URDA) based on linear programming to maximize the benefits of RSU deployment. When investigating the factors influencing RSU deployment, some scholars have considered traffic flow density [27,28], while others have considered communication factors such as transmission delay [29,30]. However, considering that there is relatively little research on permeability of CAVs in heterogeneous traffic flows when studying RSU deployment, Jiang L. et al [31] addressed the path flow reconstruction in Connected Vehicle (CV) environments while considering CAV permeability, while Salari M. et al [32] considered the CAV permeability in heterogeneous traffic flows to deploy RSUs with the aim of improving traffic prediction efficiency.…”