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A Driving Behavior Planning and Trajectory Generation Method for Autonomous Electric Bus

Author

Listed:
  • Lingli Yu

    (School of Information Science and Engineering, Central South University, Changsha 410083, China)

  • Decheng Kong

    (School of Information Science and Engineering, Central South University, Changsha 410083, China)

  • Xiaoxin Yan

    (School of Information Science and Engineering, Central South University, Changsha 410083, China)

Abstract

A framework of path planning for autonomous electric bus is presented. ArcGIS platform is utilized for map-building and global path planning. Firstly, a high-precision map is built based on GPS in ArcGIS for global planning. Then the global optimal path is obtained by network analysis tool in ArcGIS. To facilitate local planning, WGS-84 coordinates in the map are converted to local coordinates. Secondly, a double-layer finite state machine (FSM) is devised to plan driving behavior under different driving scenarios, such as structured driving, lane changing, turning, and so on. Besides, local optimal trajectory is generated by cubic polynomial, which takes full account of the safety and kinetics of the electric bus. Finally, the simulation results show that the framework is reliable and feasible for driving behavior planning and trajectory generation. Furthermore, its validity is proven with an autonomous bus platform 12 m in length.

Suggested Citation

  • Lingli Yu & Decheng Kong & Xiaoxin Yan, 2018. "A Driving Behavior Planning and Trajectory Generation Method for Autonomous Electric Bus," Future Internet, MDPI, vol. 10(6), pages 1-14, June.
    • Handle: RePEc:gam:jftint:v:10:y:2018:i:6:p:51-:d:151674
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    References listed on IDEAS

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    1. Yong-bo Chen & Guan-chen Luo & Yue-song Mei & Jian-qiao Yu & Xiao-long Su, 2016. "UAV path planning using artificial potential field method updated by optimal control theory," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(6), pages 1407-1420, April.
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    Cited by:

    1. Zhixi Hu & Yi Zhu & Xiaoying Chen & Yu Zhao, 2022. "Safety Verification of Driving Resource Occupancy Rules Based on Functional Language," Future Internet, MDPI, vol. 14(2), pages 1-15, February.

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