Obstacle avoidance path planning of intelligent electric vehicles in winding road scene

SHENG Peng-cheng; LUO Xin-wen; LI Jing-pu; WU Xue-yi; BIAN Xue-liang

doi:10.19818/j.cnki.1671-1637.2020.02.016

Volume 20 Issue 2

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Article Navigation > Journal of Traffic and Transportation Engineering > 2020 > 20(2): 195-204

SHENG Peng-cheng, LUO Xin-wen, LI Jing-pu, WU Xue-yi, BIAN Xue-liang. Obstacle avoidance path planning of intelligent electric vehicles in winding road scene[J]. Journal of Traffic and Transportation Engineering, 2020, 20(2): 195-204. doi: 10.19818/j.cnki.1671-1637.2020.02.016

Citation:

SHENG Peng-cheng, LUO Xin-wen, LI Jing-pu, WU Xue-yi, BIAN Xue-liang. Obstacle avoidance path planning of intelligent electric vehicles in winding road scene[J]. Journal of Traffic and Transportation Engineering, 2020, 20(2): 195-204. doi: 10.19818/j.cnki.1671-1637.2020.02.016

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Obstacle avoidance path planning of intelligent electric vehicles in winding road scene

doi: 10.19818/j.cnki.1671-1637.2020.02.016

1.
School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China
2.
Automotive Engineering Department, Xingtai Polytechnic College, Xingtai 054000, Hebei, China
3.
China Automotive Technology and Research Center Co., Ltd., Tianjin 300300, China

Funds:

National Key Research and Development Project of China 2017YFB0102500

Science and Technology Research Project of Hebei Universities QN2019094

More Information

Author Bio:
SHENG Peng-cheng(1983-), male, associate professor, doctoralstudent, E-mail: 570463334@qq.com

BIAN Xue-liang(1957-), male, professor, PhD, E-mail: 1723690290@qq.com
Received Date: 2019-10-19
Publish Date: 2020-04-25

Abstract

Abstract

In order to study the reliability of obstacle avoidance planning for intelligent electric vehicles in the winding road scene, a method of converting the Cartesian coordinate system into the curvilinear coordinate system was proposed. The quintic Bézier curve was used to approximate the lane line in the winding road scene to obtain the reference path. Through the arc-length parameterization of reference path, a curvilinear coordinate system was established by using the arc-length as abscissa and the lateral offset as ordinate. According to the position of the vehicle and the sub-target points in the curvilinear coordinate system, the candidate paths were generated by the cubic polynomial in real time, and the candidate paths were optimized by using the sequence quadratic planning method. In order to verify the reliability of the proposed algorithm, an electric vehicle was used as a platform to build a test car with monocular cameras, 64-line laser radar, industrial control computers and other equipments. The online simulation of vehicle obstacle avoidance algorithm in the winding road scene was implemented based on Apollo platform. During the real vehicle experiment in the zone, the GPS position error and heading angle cumulative error of the obstacle avoidance algorithm were analyzed. Research result shows that the obstacle avoidance path planning of vehicle in the winding road scene can effectively describe the information of path curvature radius, the offset distance of vehicle center from the lane line, etc, and it is easy to determine the driving area of the vehicle and the obstacle position information ahead, so as to generate the optimal path. During the obstacle avoidance in the zone, the GPS position error occurs at the initial point, turning point and obstacle avoidance point, the maximum error is 0.15 m, and the heading angle cumulative error is 12°. The sudden increase of curve position error is mainly caused by the instantaneous change of vehicle posture and the matching process of obstacles, but the error can be well controlled within a certain range. So it is feasible to solve the obstacle avoidance path planning in the winding road scene by using the curvilinear coordinate system.
- obstacle avoidance path planning,
- curvilinear coordinate system,
- quintic Bézier curve,
- sequence quadratic planning,
- winding road scene

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References(30)

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Obstacle avoidance path planning of intelligent electric vehicles in winding road scene

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