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Lane-Level Road Network Generation Techniques for Lane-Level Maps of Autonomous Vehicles: A Survey

Author

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  • Ling Zheng

    (State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China
    Engineering Research Center for Spatio-Temporal Data Smart Acquisition and Application, Ministry of Education of China, Beijing 100816, China)

  • Bijun Li

    (State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China
    Engineering Research Center for Spatio-Temporal Data Smart Acquisition and Application, Ministry of Education of China, Beijing 100816, China)

  • Bo Yang

    (State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China)

  • Huashan Song

    (Three Gorges Geotechnical Consultants Co., Ltd. Wuhan, Hubei 430074, China)

  • Zhi Lu

    (State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China)

Abstract

Autonomous driving is experiencing rapid development. A lane-level map is essential for autonomous driving, and a lane-level road network is a fundamental part of a lane-level map. A large amount of research has been performed on lane-level road network generation based on various on-board systems. However, there is a lack of analysis and summaries with regards to previous work. This paper presents an overview of lane-level road network generation techniques for the lane-level maps of autonomous vehicles with on-board systems, including the representation and generation of lane-level road networks. First, sensors for lane-level road network data collection are discussed. Then, an overview of the lane-level road geometry extraction methods and mathematical modeling of a lane-level road network is presented. The methodologies, advantages, limitations, and summaries of the two parts are analyzed individually. Next, the classic logic formats of a lane-level road network are discussed. Finally, the survey summarizes the results of the review.

Suggested Citation

  • Ling Zheng & Bijun Li & Bo Yang & Huashan Song & Zhi Lu, 2019. "Lane-Level Road Network Generation Techniques for Lane-Level Maps of Autonomous Vehicles: A Survey," Sustainability, MDPI, vol. 11(16), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:16:p:4511-:d:259362
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    References listed on IDEAS

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    1. Fraedrich, Eva & Heinrichs, Dirk & Bahamonde-Birke, Francisco J. & Cyganski, Rita, 2019. "Autonomous driving, the built environment and policy implications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 122(C), pages 162-172.
    2. Reinoso, J.F. & Moncayo, M. & Ariza-López, F.J., 2015. "A new iterative algorithm for creating a mean 3D axis of a road from a set of GNSS traces," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 118(C), pages 310-319.
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    Cited by:

    1. Zhen Yang & Ruiping Zheng & Gang Wang & Kefu Zhou, 2022. "A Dynamic Road Network Model for Coupling Simulation of Highway Infrastructure Performance and Traffic State," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    2. Jen Sim Ho & Booi Chen Tan & Teck Chai Lau & Nasreen Khan, 2023. "Public Acceptance towards Emerging Autonomous Vehicle Technology: A Bibliometric Research," Sustainability, MDPI, vol. 15(2), pages 1-18, January.
    3. Calin Iclodean & Nicolae Cordos & Bogdan Ovidiu Varga, 2020. "Autonomous Shuttle Bus for Public Transportation: A Review," Energies, MDPI, vol. 13(11), pages 1-45, June.
    4. Mohamed Alawadhi & Jumah Almazrouie & Mohammed Kamil & Khalil Abdelrazek Khalil, 2020. "A systematic literature review of the factors influencing the adoption of autonomous driving," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(6), pages 1065-1082, December.

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