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An Optimization Design of Hybrid Parking Lots in an Automated Environment

Author

Listed:
  • Taolüe Chen

    (School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Chao Sun

    (School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China)

Abstract

This paper explores the minimum lateral parking distance and parking acceleration/deceleration distance of vehicles to improve the efficiency of automated valet parking (AVP) lots and save urban land. Specifically, the paper focuses on designing parking lots for automated guided vehicles (AGVs) and their parking attributes. To ensure AGV accessibility and maximize AVP capacity, graph theories and unique path-driving methods are used in designing mobile priority parking lots and decision spaces. Additionally, the paper proposes an optimization design for parking lots with obstacles, considering the layout of load-bearing columns and charging resources for electric vehicles in underground parking lots. The article further proposes an optimization design for hybrid parking lots based on spatio-temporal resource conversion in traffic design and the principle of traffic separation in traffic control since hybrid parking lots that accommodate both conventional vehicles and AGVs are crucial to the future development of urban parking lots. The experimental results show that the proposed optimization design for urban parking lots in automated environments is superior to the traditional parking lots design in terms of capacity and density. This paper provides an optimal layout scheme of urban parking lots in multiple scenarios, which can improve the service level of urban static traffic systems.

Suggested Citation

  • Taolüe Chen & Chao Sun, 2023. "An Optimization Design of Hybrid Parking Lots in an Automated Environment," Sustainability, MDPI, vol. 15(21), pages 1-19, October.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:21:p:15475-:d:1271483
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    References listed on IDEAS

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    1. Millard-Ball, Adam, 2019. "The autonomous vehicle parking problem," Transport Policy, Elsevier, vol. 75(C), pages 99-108.
    2. Nourinejad, Mehdi & Bahrami, Sina & Roorda, Matthew J., 2018. "Designing parking facilities for autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 110-127.
    3. Zakharenko, Roman, 2016. "Self-driving cars will change cities," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 26-37.
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    Cited by:

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    2. Ting Wan & Jibo Gao, 2025. "Analyzing Traffic Operation Characteristics of Cold-Climate Cities Based on Multi-Source Data Fusion: A Case Study of Harbin," Sustainability, MDPI, vol. 17(4), pages 1-18, February.

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