An Integrated Vehicle Navigation System Utilizing Lane-Detection and Lateral Position Estimation Systems in Difficult Environments for GPS

IEEE Transactions on Intelligent Transportation Systems(2014)

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摘要
A navigation filter combines measurements from sensors currently available on vehicles - Global Positioning System (GPS), inertial measurement unit, inertial measurement unit (IMU), camera, and light detection and ranging (lidar) - for achieving lane-level positioning in environments where stand-alone GPS can suffer or fail. Measurements from the camera and lidar are used in two lane-detection systems, and the calculated lateral distance (to the lane markings) estimates of both lane-detection systems are compared with centimeter-level truth to show decimeter-level accuracy. The navigation filter uses the lateral distance measurements from the lidar- and camera-based systems with a known waypoint-based map to provide global measurements for use in a GPS/Inertial Navigation System (INS) system. Experimental results show that the inclusion of lateral distance measurements and a height constraint from the map creates a fully observable system even with only two satellite observations and, as such, greatly enhances the robustness of the integrated system over GPS/INS alone. Various scenarios are presented, which affect the navigation filter, including satellite geometry, number of satellites, and loss of lateral distance measurements from the camera and lidar systems.
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关键词
Global Positioning System,Kalman filters,cameras,inertial navigation,object detection,road vehicles,Global Positioning System,IMU,INS,Kalman filter,LIDAR,camera,camera-based systems,centimeter-level truth,decimeter-level accuracy,height constraint,inertial measurement unit,inertial navigation system system,integrated vehicle navigation system,lane-detection systems,lane-level positioning,lateral distance,lateral distance measurements,lateral position estimation systems,light detection and ranging,navigation filter,satellite observations,sensors,stand-alone GPS,waypoint-based map,Camera,Global Navigation Satellite System,Global Positioning System (GPS),Kalman filter,inertial measurement unit (IMU),lane detection,light detection and ranging (lidar),outages,sensor fusion
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