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Estimation of Vehicle Pose and Position with Monocular Camera at Urban Road Intersections

Author(s)
Yuan, Jin-Zhao; Chen, Hui; Zhao, Bin; Xu, Yanyan
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Abstract
With the rapid development of urban, the scale of the city is expanding day by day. The road environment is becoming more and more complicated. The vehicle ego-localization in complex road environment puts forward imperative requirements for intelligent driving technology. The reliable vehicle ego-localization, including the lane recognition and the vehicle position and attitude estimation, at the complex traffic intersection is significant for the intelligent driving of the vehicle. In this article, we focus on the complex road environment of the city, and propose a pose and position estimation method based on the road sign using only a monocular camera and a common GPS (global positioning system). Associated with the multi-sensor cascade system, this method can be a stable and reliable alternative when the precision of multi-sensor cascade system decreases. The experimental results show that, within 100 meters distance to the road signs, the pose error is less than 2 degrees, and the position error is less than one meter, which can reach the lane-level positioning accuracy. Through the comparison with the Beidou high-precision positioning system L202, our method is more accurate for detecting which lane the vehicle is driving on.
Date issued
2017-12
URI
http://hdl.handle.net/1721.1/113347
Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Journal
Journal of Computer Science and Technology
Publisher
Springer US
Citation
Yuan, Jin-Zhao, et al. “Estimation of Vehicle Pose and Position with Monocular Camera at Urban Road Intersections.” Journal of Computer Science and Technology, vol. 32, no. 6, Nov. 2017, pp. 1150–61.
Version: Final published version
ISSN
1000-9000
1860-4749

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