Abstract—Autonomous driving requires continuous and reliable centimeter level positioning accuracy for acceptable lane level navigational performance. Centimeter level positioning accuracy cannot be achieved using a conventional DGPS/DR. To deal with the above problem this paper proposes the novel and effective bias/shift estimation of DGPS/DR. On this paper, a surveyed precise map is used that is consisting of waypoints with centimeter level positioning accuracy for the lateral and longitudinal directions. The time history of DGPS/DR waypoints are compared with the closest set of waypoints from surveyed precise map. Both a straight line fitting method and a sliding curve method have been used in order to match the shape of the DGPS/DR trajectory with surveyed precise map. For lateral and longitudinal DGPS/DR bias estimation, we have adopted a disturbance observer. Finally, experiments were conducted to prove the feasibility of the proposed algorithm for the shift estimation of DGPS/DR. This paper also compares the experimental results of GPS/DR with the ones using RTK GPS/DR during autonomous driving.
Index Terms—RTKt, DGPS bias, Map based DGPS bias estimation, DGPS based autonomous driving.
S. S. Rathour, Ali Boyali, Lyu Zheming, Seiichi Mita, Vijay John are with Research Center for Smart Vehicle, Toyota Technological Institute, Nagoya, Japan (e-mail: {swarn,ali, smita, vijayjohn}@toyota-ti.ac.jp, lvzheming@gmail.com).
Cite: S. S. Rathour, Ali Boyali, Lyu Zheming, Seiichi Mita, and Vijay John, "A Map-based Lateral and Longitudinal DGPS/DR Bias Estimation Method for Autonomous Driving," International Journal of Machine Learning and Computing vol. 7, no. 4, pp. 67-71, 2017.