? 基于单目相机的交通路口车辆姿态和位置估计
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Journal of Computer Science and Technology 2017, Vol. 32 Issue (6) :1150-1161    DOI: 10.1007/s11390-017-1790-3
Special Section of CAD/Graphics 2017 << Previous Articles | Next Articles >>
基于单目相机的交通路口车辆姿态和位置估计
Jin-Zhao Yuan1, Hui Chen1,*, Bin Zhao2, Yanyan Xu3,
1 School of Information Science and Engineering, Shandong University, Jinan 250100, China;
2 Beijing Xuanlongding-xun Technology Co., Ltd., Beijing 100041, China;
3 Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge 02139, U.S.A
Estimation of Vehicle Pose and Position with Monocular Camera at Urban Road Intersections
Jin-Zhao Yuan1, Hui Chen1,*, Bin Zhao2, Yanyan Xu3,
1 School of Information Science and Engineering, Shandong University, Jinan 250100, China;
2 Beijing Xuanlongding-xun Technology Co., Ltd., Beijing 100041, China;
3 Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge 02139, U.S.A

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摘要 目前城市发展速度和规模不断加快扩大,道路环境愈加错综复杂,复杂道路环境对智能驾驶技术的可靠性提出了更高的要求。车辆在复杂交通路口的精准自我定位、车道识别和车辆姿态估计对车辆智能驾驶尤其重要。本文针对城市复杂道路环境,研究提出一种基于道路标识牌和普通GPS的车载单目相机位姿估计方法。与多传感器级联系统结合使用,本文提出的方法可在其精度下降时,为自动驾驶提供另一种稳定可靠的定位来源和数据参考。实验结果表明,本文方法能够在距离标识牌100米之内,姿态误差小于2°,定位误差小于1米,可以达到车道级定位精度。比较于北斗高精度定位系统L202,本文方法能够更精确地确定车辆所行驶的车道。
关键词车辆姿态和位置估计   道路标识牌检测   单一性矩阵   交叉路口   城市环境     
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.
Keywordsehicle pose and position estimation   road sign detection   homograph matrix   road intersection   urban environment     
Received 2017-06-24;
本文基金:

This work was supported by the Key Project of National Natural Science Foundation of China under Grant No. 61332015 and the Natural Science Foundation of Shandong Province of China under Grant Nos. ZR2013FM302 and ZR2017MF057.

通讯作者: Yanyan Xu     Email: yanyanxu@mit.edu
About author: Jin-Zhao Yuan is a postgraduate student at the School of Information Science and Engineering in Shandong University,Jinan.His research interests include autonomous driving,camera calibration,and 3D vision analysis.
引用本文:   
Jin-Zhao Yuan, Hui Chen, Bin Zhao, Yanyan Xu.基于单目相机的交通路口车辆姿态和位置估计[J]  Journal of Computer Science and Technology , 2017,V32(6): 1150-1161
Jin-Zhao Yuan, Hui Chen, Bin Zhao, Yanyan Xu.Estimation of Vehicle Pose and Position with Monocular Camera at Urban Road Intersections[J]  Journal of Computer Science and Technology, 2017,V32(6): 1150-1161
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http://jcst.ict.ac.cn:8080/jcst/CN/10.1007/s11390-017-1790-3
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