Cooperative vehicle positioning with multi-sensor data fusion and vehicular communications

Vehicular positioning with multi-sensor fusion has achieved promising results in recent years. Having potential benefit from the emerging vehicular communications based on IEEE 802.11p dedicated short-range communication (DSRC), cooperative positioning opens new opportunities to support several vehicular applications. In addition, radar based active safety functions and GPS are being integrated into modern vehicles. With the availability of information from multiple sources, exchange of sensor information and multi-sensor fusion can be applied to obtain the precise positioning of vehicle without substantial additional cost. However, the main challenge in data fusion is the inherent data association problem due to dissimilar measurement update rate of DSRC and automotive radar. To overcome these challenges, this paper proposes a robust positioning approach considering track-to-track matching and fusion of position information obtained from multiple on-board sources such as GPS receiver, Vehicle-to-vehicle communication and automotive radar. Realistic 3D road traffic and wave propagation model is developed using a ray-tracing tool and the effectiveness of the proposed concept was evaluated. The system concept is validated by conducting extensive simulation considering realistic car following model. Results show that the proposed cooperative positioning method exhibits significant improvement in terms of positioning accuracy.