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Path Tracking and Local Obstacle Avoidance for Automated Vehicle Based on Improved Artificial Potential Field

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Abstract

This study proposes an improved artificial potential field (APF) by considering the cooperative control of local obstacle avoidance and path tracking for automated vehicles. We established the path gravitational potential field (GPF) based on the scheduled path (SP), including the lateral and longitudinal GPFs, to enable the automated vehicle to quickly return to the SP and track after obstacle avoidance, while maintaining control of speed for the entire process. To address the local optimal solution problem of the classical APF, we proposed a sub-target-point selection strategy based on the information of obstacles and SP and established the GPF of the sub-target points. Thus, the automated vehicle can avoid obstacles and quickly return to the SP. Furthermore, the relative velocity of the automated vehicle and the obstacle was used to establish the velocity repulsion potential field (RPF), which improved the adaptability of the APF to dynamic obstacles. The simulation results indicate that the improved APF is capable of cooperative control of path tracking and local obstacle avoidance.

Code is available at https://github.com/xiaowang617/Improve-APF.

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Authors and Affiliations

  1. Harbin Institute of Technology-Weihai, Weihai, China

    Weihua Li, Yipeng Wang, Junlong Guo, Dianbo Ren & Jianfeng Wang

  2. HIT Wuhu Robot Technology Research Institute, Wuhu, China

    Weihua Li

  3. State Grid Electric Vehicle Service Hunan Company Ltd., Hunan, China

    Shengkai Zhu, Jianping Xiao & Shijuan Chen

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  1. Weihua Li
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Corresponding author

Correspondence to Junlong Guo.

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Conflict of Interest

The authors declare that they have no conflict of interest.

Weihua Li is an associate professor at the School of Automotive Engineering in Harbin Institute of Technology (Weihai). He received his B.Sc., M.Sc., and Ph.D. degrees in manufacturing engineering of aerospace vehicle from Harbin Institute of Technology in 2009, 2011, and 2016, respectively. His research interests include dynamics and control of mobile robots.

Yipeng Wang is currently a master’s degree candidate at the School of Automotive Engineering in Harbin Institute of Tech-nology (Weihai). He received his B.Sc. degree in automotive engineering from Shandong University of Science and Technology in 2019. His research interests include control of mobile manipulators and autonomous vehicles.

Shengkai Zhu is a senior economist of State Grid Electric Vehicle Service Hunan Company LTD. He received his bachelor’s degree in industrial management engineering from Hunan University in 1999. His research interests include electric vehicles.

Jianping Xiao is a Senior engineer of State Grid Electric Vehicle Service Hunan Company LTD. He received his bachelor’s degree in power system and automation from Wuhan University of Hydraulic and Electric Power in 1995. His research interests include electric vehicles.

Shijuan Chen is an engineer at State Grid Electric Vehicle Service Hunan Company LTD. She received her bachelor’s degree in electrical engineering and automation from Chongqing University in 2011. Her research interests include electric vehicles.

Junlong Guo is an associate professor in Harbin Institute of Technology (Wei-hai). He received his B.S., M.S., and Ph.D. degrees in manufacturing engineering of aerospace vehicle from Harbin Institute of Technology, Harbin, China, in 20011, 2013, and 2018, respectively. His research interests include terramechanics and motion control of wheeled mobile robots.

Dianbo Ren is an associate professor at the School of Automotive Engineering in Harbin Institute of Technology (Weihai). He received his Ph.D. degree in transportation information engineering and control from Southwest Jiaotong University in 2008. His research interests include path planning and control of automotive vehicles.

Jianfeng Wang is a professor at the School of Automotive Engineering in Harbin Institute of Technology (Weihai). He received his Ph.D. degree in mechanical engineering from Harbin Institute of Technology in 2018. His research interests include design, simulation, and control of automotive vehicles.

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This work was supported by the National Natural Science Foundation of China (52175007/52175012), the HIT Wuhu Robot Technology Research Institute (HIT-CXY-CMP2-ADTIL-21-01), the China Postdoctoral Science Foundation (2018M630348), the Self-Planned Task (NO. SKLRS202005B) of State Key Laboratory of Robotics and System (HIT).

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Li, W., Wang, Y., Zhu, S. et al. Path Tracking and Local Obstacle Avoidance for Automated Vehicle Based on Improved Artificial Potential Field. Int. J. Control Autom. Syst. 21, 1644–1658 (2023). https://doi.org/10.1007/s12555-022-0183-8

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