Open AccessOptimisation strategy of roadside units deployment towards VANET localisation with dead reckoning
Author(s) -
Zhang Rui,
Yan Feng,
Zhu Yaping,
Xia Weiwe,
Zhang Shanjie,
Shen Lianfeng
Publication year - 2020
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2019.0814
Subject(s) - software deployment , computer science , dilution of precision , vehicular ad hoc network , particle swarm optimization , dead reckoning , convergence (economics) , interval (graph theory) , wireless ad hoc network , stability (learning theory) , real time computing , algorithm , telecommunications , wireless , global positioning system , mathematics , machine learning , gnss applications , combinatorics , economics , economic growth , operating system
In vehicle ad‐hoc networks (VANETs), the full coverage of roadside units (RSUs) is not necessary with the assistance of dead reckoning (DR) for the RSU‐based vehicle localisation. This study proposes an optimisation strategy of RSUs deployment, which seeks an optimal RSU layout ensuring the best localisation accuracy with a minimum number of RSUs. With the assistance of DR, first, the average geometric dilution of precision (GDOP) for a specific localisation region is derived through a non‐linear recursive model. Then the RSUs deployment is formulated into an optimisation problem, and the objective is as a function of the average GDOP and deploying interval. Finally, the optimisation problem is solved by a centre particle swarm optimisation (CPSO) algorithm. The convergence and stability of CPSO are evaluated via simulations. Furthermore, simulations also show that the proposed strategy can optimise the localisation accuracy of RSUs deployment in the VANET scenario.