Research On Location Method Of Driverless Vehicle Based On MAP Matching

The acquisition of accurate localization in vehicle is a key issue for driverless cars during driving.At present,the Global Positioning System(GPS)is widely used as a vehicle positioning method,which can obtain global positioning coordinates in a wide range of outdoor open areas,but there are problems of poor local positioning accuracy or loss of positioning in indoor or outdoor occlusion environments.Therefore,in this paper the positioning estimation of driverless cars is studied,and the GPS and map matching combination positioning method is proposed to improve the positioning accuracy of driverless vehicles in a wide range of complex scenes.The main work of this paper is as follows:Firstly,the GPS positioning error characteristics and data preprocessing techniques are studied.The advantages and disadvantages of GPS positioning technology are analyzed.Based on real-time data filtering technology,a data filtering method is used to reduce the GPS interference error.Secondly,the vehicle kinematics model is established and the vehicle trajectory estimation algorithm is studied.The advantages and disadvantages of the trajectory estimation are analyzed.Based on the unscented kalman filter technology,a method which fuse GPS and trajectory estimation is proposed,and it improve the vehicle positioning accuracy.At the same time,based on the vehicle kinematics model,a new kinematics model for correcting the track estimation error is established for the problem of track estimation error interference in mobile platform.Based on the model,a track estimation correction algorithm is proposed to reduce the track estimation error.Finally,the SLAM technology which used single-line lidar is studied.The improved FastSLAM algorithm based on RBPF and the two-dimensional map matching localization algorithm are analyzed.The composition experiments are carried out in indoor and outdoor environments.After the indoor and outdoor two-dimensional environment map are obtained,a method which combine GPS,trajectory estimation and map matching is proposed by the map matching technology,so higher precision positioning of the driverless vehicle is achieved in a large-scale indoor and outdoor complex scene.The experimental results show that the positioning method proposed in this paper cansolve the problem of vehicle positioning in large-scale indoor and outdoor complex scenes and improve the positioning accuracy of the vehicle.Compared with the traditional GPS positioning method,it has the advantages of wide positioning range and high positioning accuracy.