An Integrated Vehicle Navigation System Utilizing Lane-Detection and Lateral Position Estimation Systems in Difficult Environments for GPS. Rose, C., Britt, J., Allen, J., & Bevly, D. IEEE Transactions on Intelligent Transportation Systems, 15(6):2615–2629, December, 2014. ![An Integrated Vehicle Navigation System Utilizing Lane-Detection and Lateral Position Estimation Systems in Difficult Environments for GPS [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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.
@article{rose_integrated_2014,
title = {An {Integrated} {Vehicle} {Navigation} {System} {Utilizing} {Lane}-{Detection} and {Lateral} {Position} {Estimation} {Systems} in {Difficult} {Environments} for {GPS}},
volume = {15},
issn = {1558-0016},
url = {https://ieeexplore.ieee.org/document/6822610/;jsessionid=42809654FABB8393AAD6EA28E0658F60},
doi = {10.1109/TITS.2014.2321108},
abstract = {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.},
number = {6},
urldate = {2024-06-20},
journal = {IEEE Transactions on Intelligent Transportation Systems},
author = {Rose, Christopher and Britt, Jordan and Allen, John and Bevly, David},
month = dec,
year = {2014},
keywords = {Camera, Cameras, Global Navigation Satellite System, Global Positioning System, Global Positioning System (GPS), Image edge detection, Kalman filter, Kalman filters, Sensor fusion, inertial measurement unit (IMU), lane detection, light detection and ranging (lidar), outages, sensor fusion},
pages = {2615--2629},
}
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