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Research on eVTOL Air Route Network Planning Based on Improved A* Algorithm

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  • Mian Ye

    (School of Aeronautics and Astronautics, Xihua University, Chengdu 610039, China
    Engineering Research Center of Ministry of Education for Intelligent Air-Ground Integration Vehicles and Control, Chengdu 610039, China
    These authors contributed equally to this work.)

  • Jinchen Zhao

    (School of Aeronautics and Astronautics, Xihua University, Chengdu 610039, China
    Engineering Research Center of Ministry of Education for Intelligent Air-Ground Integration Vehicles and Control, Chengdu 610039, China
    These authors contributed equally to this work.)

  • Quanli Guan

    (School of Aeronautics and Astronautics, Xihua University, Chengdu 610039, China)

  • Xuejun Zhang

    (School of Electronic Information Engineering, Beihang University, Beijing 100191, China)

Abstract

With the continuous opening of low-altitude airspace and the development of aircraft such as electric vertical takeoff and landing (eVTOL) vehicles, urban air traffic has become a sustainable and green development direction for future transportation. Air route networks, as a mainstream design scheme for air traffic, are able to provide prerequisites for eVTOL and other green aircraft to enter urban airspace for safe operation, among which air route planning is a fundamental component of air route network design. Currently, most of the research on aircraft path planning is performed in free airspace, lacking the analysis and processing for the complex operation environment, which has led to the high risk and large operation cost of path planning results, failing to meet the demand for safe and efficient development in the future. Aiming at the above problems, eVTOL-oriented air route planning research was carried out. Firstly, the urban low-altitude airspace structure was planned, and the operational levels of eVTOL were clarified; this was followed by introducing the urban dynamic air–ground risk factors and constructing a dynamic risk assessment model containing risk level information; finally, the improved A* algorithm based on the risk cost was employed to plan the eVTOL air route network, which finally realized the purpose of short path length and low total risk. The simulation results showed that the route generated by the improved A* algorithm could reduce the risk cost by at least 30% with a relatively small path cost, which ensured the operation efficiency and safety of eVTOLs and laid the foundation for the further sustainable and green development of urban airspace in the future.

Suggested Citation

  • Mian Ye & Jinchen Zhao & Quanli Guan & Xuejun Zhang, 2024. "Research on eVTOL Air Route Network Planning Based on Improved A* Algorithm," Sustainability, MDPI, vol. 16(2), pages 1-30, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:2:p:561-:d:1315717
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    References listed on IDEAS

    as
    1. Peng Han & Xinyue Yang & Yifei Zhao & Xiangmin Guan & Shengjie Wang, 2022. "Quantitative Ground Risk Assessment for Urban Logistical Unmanned Aerial Vehicle (UAV) Based on Bayesian Network," Sustainability, MDPI, vol. 14(9), pages 1-13, May.
    2. Gonçalves, P. & Sobral, J. & Ferreira, L.A., 2017. "Unmanned aerial vehicle safety assessment modelling through petri Nets," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 383-393.
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