Evolutionary Coalitional Game-Based Cooperative Localization in Vehicular Networks

Abstract

Cooperative localization under complex urban environments has become a solution able to replace Global Navigation Satellite System (GNSS) positioning. Due to the lack of an efficient cooperative localization scheme, traditional cooperative vehicle networks result in high computational complexity and heavy communication overhead. In this paper, we concentrate on the cooperative localization design of a vehicle. This paper proposes a cooperative localization method based on evolutionary coalitional game theory to implement vehicle location estimation with a lower communication cost. We select the neighboring vehicles to form a coalition based on the node’s square position error bound and communication cost. The location is obtained via exchanging information between vehicles. It is evident from the simulations and results that the proposed method requires a low communication overhead while maintaining localization accuracy.