Abstract— In this paper a novel approach for improving vehicular positioning is presented. This method is based on the cooperation of the vehicles by communicating their measured information about their position. This method consists of two steps. In the first step we introduce our cooperative map matching method. This map matching method uses the V2V communication in a VANET to exchange GPS information between vehicles. Having a precise road map, vehicles can apply the road constraints of other vehicles in their own map matching process and acquire a significant improvement in their positioning. After that we have proposed the concept of a dynamic base station DGPS (DDGPS) which is used by vehicles in the second step to generate and broadcast the GPS pseudorange corrections which can be used by newly arrived vehicles to improve their positioning. The DDGPS is a decentralized cooperative method which aims to improve the GPS positioning by estimating and compensating the common error in GPS pseudorange measurements. It can be seen as an extension of DGPS where the base stations are not necessarily static with an exact known position. In the DDGPS method, the pseudorange corrections are estimated, based on the receiver’s belief on its positioning and its uncertainty, and then broadcasted to other GPS receivers. The performance of the proposed algorithm has been verified with simulations in several realistic scenarios. Index Terms— Cooperative Map Matching; Cooperative Vehicle Positioning; GPS; VANET; DDGPS; Intelligent Vehicles I. INTRODUCTION avigation systems constitute an essential component of intelligent vehicles and are being used in a great variety of active or informative ADAS applications. GNSS based navigation systems allow to easily obtain information on the absolute position of the vehicle and their use are widely spread in ITS applications [1]. However, low cost GPS receiver- This paper was submitted for review on December 1, 2014. Research supported by NSERC of Canada and ANR of France. M. Rohani and D. Gingras are with the Electrical and Computer Engineering Department, Université de Sherbrooke, Sherbrooke, Qc J1K 2R1 Canada,(email:mohsen.rohani@usherbrooke.ca, denis.gingras@usherbrooke.ca). D. Gruyer, is with the IFSTTAR- IM - LIVIC, 14 route de la minière, bat. 824, 78000 Versailles-Satory, France, (email: dominique.gruyer@ifsttar.fr) based navigation systems used in automotive applications suffer from low accuracy and frequent signal outages. Typically, the GPS nominal accuracy is about 15m, which is usually not sufficient for active safety and ADAS applications such as lane level positioning. One of the most common ways to improve accuracy for ego-localization is to use other embedded sources of information and to combine them with GNSS data. Those other sources can be dead reckoning sensors, such as INS and odometer, or video cameras [2, 3]. This approach typically use data fusion algorithms, like Kalman filters or particle filters [4] to combine the information of those different sensors in order to obtain a better position estimate than the one obtained by the GPS receiver alone or by each of the individual sensor. A classical approach to enhance the GPS positioning accuracy is to use a differential method exploiting a fixed known position as a ground based reference, hence the name differential GPS (DGPS) [5]. In DGPS, the ground based reference station with an exactly known position, broadcasts its GPS receiver information, which allows to calculate and correct the errors of the measured pseudoranges obtained by other non-fixed GPS receivers in the vicinity. The method exploits the fact that GPS receivers, which are close to each other, are affected by the various sources of errors in a similar way. This assumption can be done because of the use of the same set of satellites in order to assess ego-localization. To apply this approach in the real world and with static road side stations it requires to deploy a large number of reference stations in order to be able to enhance the GPS position in a given region. This approach is therefore very expensive in terms of infrastructure. In addition DGPS to operate properly always requires a communication link between the reference stations and the mobile GPS receivers. These two constraints make the DGPS approach difficult to implement and also very expensive to use for general vehicle positioning in automotive applications. Map matching is a method which is widely used in vehicular satellite based navigation systems. Conventionally, it has been used to estimate the vehicle position on a digital road map, using GPS and motion sensors data as input to the map matching algorithm. However, the improvement of digital maps quality in recent years has brought the possibility A Novel approach for Improved Vehicular Positioning using Cooperative Map Matching and Dynamic base station DGPS concept M. Rohani, D. Gingras, D. Gruyer N