Estimation of Vehicle Pose and Position with Monocular Camera at Urban Road Intersections
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-l...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer-Verlag
2018
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| Online Access: | http://hdl.handle.net/1721.1/114687 |
| _version_ | 1826213861287526400 |
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| author | Yuan, Jin-Zhao Chen, Hui Zhao, Bin Xu, Yanyan |
| author2 | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Yuan, Jin-Zhao Chen, Hui Zhao, Bin Xu, Yanyan |
| author_sort | Yuan, Jin-Zhao |
| collection | MIT |
| description | 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. Keywords: vehicle pose and position estimation; road sign detection; homograph matrix; road intersection; urban environment |
| first_indexed | 2024-09-23T15:56:00Z |
| format | Article |
| id | mit-1721.1/114687 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:56:00Z |
| publishDate | 2018 |
| publisher | Springer-Verlag |
| record_format | dspace |
| spelling | mit-1721.1/1146872022-10-02T05:10:03Z Estimation of Vehicle Pose and Position with Monocular Camera at Urban Road Intersections Yuan, Jin-Zhao Chen, Hui Zhao, Bin Xu, Yanyan Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Xu, Yanyan 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. Keywords: vehicle pose and position estimation; road sign detection; homograph matrix; road intersection; urban environment 2018-04-12T19:54:29Z 2018-04-12T19:54:29Z 2017-12 2017-09 2017-12-07T07:04:27Z Article http://purl.org/eprint/type/JournalArticle 1000-9000 1860-4749 http://hdl.handle.net/1721.1/114687 Yuan, Jin-Zhao et al. “Estimation of Vehicle Pose and Position with Monocular Camera at Urban Road Intersections.” Journal of Computer Science and Technology 32, 6 (November 2017): 1150–1161 © 2017 Springer Science + Business Media, LLC & Science Press en http://dx.doi.org/10.1007/s11390-017-1790-3 Journal of Computer Science and Technology Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ Springer Science+Business Media, LLC & Science Press, China application/pdf Springer-Verlag Springer US |
| spellingShingle | Yuan, Jin-Zhao Chen, Hui Zhao, Bin Xu, Yanyan Estimation of Vehicle Pose and Position with Monocular Camera at Urban Road Intersections |
| title | Estimation of Vehicle Pose and Position with Monocular Camera at Urban Road Intersections |
| title_full | Estimation of Vehicle Pose and Position with Monocular Camera at Urban Road Intersections |
| title_fullStr | Estimation of Vehicle Pose and Position with Monocular Camera at Urban Road Intersections |
| title_full_unstemmed | Estimation of Vehicle Pose and Position with Monocular Camera at Urban Road Intersections |
| title_short | Estimation of Vehicle Pose and Position with Monocular Camera at Urban Road Intersections |
| title_sort | estimation of vehicle pose and position with monocular camera at urban road intersections |
| url | http://hdl.handle.net/1721.1/114687 |
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