Cooperative vehicle safety can help prevent vehicle collisions by providing timely warnings to the driver or initiating automatic preventive actions based on vehicle dynamics information exchanged between vehicles. The information is shared wirelessly through the emerging DSRC (Dedicated Short Range Communication) standards. The vehicle dynamics information that is shared, such as vehicle velocity and location, is collected from the vehicle's internal sensor communication network and from Global Navigation Satellite Systems (GNSS), which includes the Global Positioning System (GPS). GNSS is a critical component of this safety system since it has the needed ability to accurately determine a vehicle's location coordinates in most driving environments. However, its performance can suffer from obstructions in dense urban areas.Deficiencies of GNSS can be overcome by complimenting GNSS with other sensors. The system presented here combines GPS, Inertial Measurement Unit (IMU), odometer, and laser measurements to achieve lane-level positioning accuracy even in deep urban canyons. This paper introduces the sensor fusion algorithm used to produce the positioning solution, the selection of the optimal sensor suite through simulation, and the performance analysis using test data from a difficult real-world environment.