Roadside Units Non-full Coverage Optimization Deployment Based on Simulated Annealing Particle Swarm Optimization Algorithm

Abstract

This paper studies a scheme for optimal deployment of roadside units (RSU) with non-full coverage in the Vehicular Ad-hoc Network (VANET). The goal of RSU Deployment Optimization (RDO) is to achieve the best economic benefit between the deployment cost and the vehicle's need for positioning accuracy. That is, when the positioning accuracy of the vehicle keeps at an acceptable threshold, the number of deployed RSU is minimized. So an efficient RSU deployment pattern is one of the core aspects that must be considered in the designing of VANET. The paper first analyzes the cumulative error estimation based on the Inertial Navigation System (INS) when the vehicle travels in the Non-covered Area (NCA) of the road, and formulates the deployment model with reference to the coverage radius of RSU. Since the optimal solution for RDO is a NP-hard problem, another contribution of this paper is to use Geometric Dilution of Precision (GDOP) to evaluate the positioning error in NCA, and then to propose a heuristic algorithm to solve the problem. The simulation results show that the proposed scheme can effectively solve the medium-sized optimization problem of road incomplete coverage.