Cooperative localization based on topology matching

In this paper, we propose a new vehicle localization method based on topology matching in mutli-vehicle enviroment. Each vehicle is assumed to generate a local map which is a set of position measurements of nearby vehicles by using onboard low-cost GPS and ranging sensors, and share it with others by broadcasting via vehicle-to-vehicle(V2V) communication. When a vehicle receives multiple local maps from neighbors, it incorporates and fuses them with its own local map by using a local map matching algorithm. The proposed algorithm is based on the topology matching technique and the multi-sensor Kalman filter. Simulation results show that our method can extend the detection range and improve the position accuracy by 65% compared to conventional localization methods utilizing the Kalman filter with only onboard GPS measurements.