IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i10p4145-d1395167.html
   My bibliography  Save this article

Eco-Friendly Smart Car Parking Management System with Enhanced Sustainability

Author

Listed:
  • Nazmus Sakib

    (Graduate School of Science and Technology, Gunma University, Kiryu 376-8515, Japan)

  • A. S. M. Bakibillah

    (Department of Systems and Control Engineering, Tokyo Institute of Technology, Tokyo 152-8552, Japan)

  • Susilawati Susilawati

    (School of Engineering, Monash University, Bandar Sunway, Subang Jaya 47500, Malaysia)

  • Md Abdus Samad Kamal

    (Graduate School of Science and Technology, Gunma University, Kiryu 376-8515, Japan)

  • Kou Yamada

    (Graduate School of Science and Technology, Gunma University, Kiryu 376-8515, Japan)

Abstract

Efficient car parking management systems that minimize environmental impacts while maximizing user comfort are highly demanding for a future sustainable society. Using electric or gasoline vehicle-type information, emerging computation and communication technologies open the opportunity to provide practical solutions to achieve such goals. This paper proposes an eco-friendly smart parking management system that optimally allocates the incoming vehicles to reduce overall emissions in closed parking facilities while providing comfort incentives to the users of electric vehicles (EVs). Specifically, upon arrival of a car, the most suitable parking spot is determined by minimizing an adaptive objective function that indirectly reflects anticipatory operation for the overall performance maximization of the parking facility using electric or gasoline vehicle-type information. The adaptive objective function includes a trade-off factor that tunes driving and walking distances, relating emissions and comfort to treat incoming vehicles appropriately. The proposed system is simulated for managing a model car parking facility in a shopping complex in Japan, and the aspects related to fuel consumption, CO 2 emissions, and user comfort are evaluated and benchmarked with other standard parking management systems. The proposed system reduces CO 2 emissions and fuel consumption and improves parking efficiency compared to the current parking management systems, while also prioritizing user comfort.

Suggested Citation

  • Nazmus Sakib & A. S. M. Bakibillah & Susilawati Susilawati & Md Abdus Samad Kamal & Kou Yamada, 2024. "Eco-Friendly Smart Car Parking Management System with Enhanced Sustainability," Sustainability, MDPI, vol. 16(10), pages 1-14, May.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:4145-:d:1395167
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/10/4145/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/10/4145/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lei, Chao & Zhang, Qian & Ouyang, Yanfeng, 2017. "Planning of parking enforcement patrol considering drivers’ parking payment behavior," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 375-392.
    2. Wang, Xiaotian & Wang, Xin, 2019. "Flexible parking reservation system and pricing: A continuum approximation approach," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 408-434.
    3. Wang, Pengfei & Guan, Hongzhi & Liu, Peng, 2020. "Modeling and solving the optimal allocation-pricing of public parking resources problem in urban-scale network," Transportation Research Part B: Methodological, Elsevier, vol. 137(C), pages 74-98.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marianne Guillet & Maximilian Schiffer, 2022. "Coordinating charging request allocation between self-interested navigation service platforms," Papers 2208.09530, arXiv.org.
    2. Dixit, Aasheesh Kumar & Shakya, Garima & Jakhar, Suresh Kumar & Nath, Swaprava, 2023. "Algorithmic mechanism design for egalitarian and congestion-aware airport slot allocation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).
    3. Lu, Xiao-Shan & Huang, Hai-Jun & Guo, Ren-Yong & Xiong, Fen, 2021. "Linear location-dependent parking fees and integrated daily commuting patterns with late arrival and early departure in a linear city," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 293-322.
    4. Zipeng Zhang & Ning Zhang, 2021. "Early Bird Scheme for Parking Management: How Does Parking Play a Role in the Morning Commute Problem," Sustainability, MDPI, vol. 13(15), pages 1-19, July.
    5. Ferreira, Reinaldo & Móra, Vasco & Mourão, Maria Cândida & Moz, Margarida & Pinto, Leonor S. & Ribeiro, João, 2022. "Arc Routing for Parking Enforcement Officers: Exact and heuristic solutions," European Journal of Operational Research, Elsevier, vol. 299(1), pages 283-301.
    6. Xie, Minghui & Zhang, Xinying & Wu, Zhouhao & Wei, Sen & Gao, Yanan & Wang, Yuanqing, 2023. "A shared parking optimization framework based on dynamic resource allocation and path planning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 616(C).
    7. Macea, Luis F. & Serrano, Iván & Carcache-Guas, Camila, 2023. "A reservation-based parking behavioral model for parking demand management in urban areas," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    8. Yunqiang Xue & Qifang Kong & Feng Sun & Meng Zhong & Haokai Tu & Caifeng Tan & Hongzhi Guan, 2022. "Shared Parking Decision Behavior of Parking Space Owners and Car Travelers Based on Prospect Theory—A Case Study of Nanchang City, China," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    9. Zhou, Xizhen & Lv, Mengqi & Ji, Yanjie & Zhang, Shuichao & Liu, Yong, 2023. "Pricing curb parking: Differentiated parking fees or cash rewards?," Transport Policy, Elsevier, vol. 142(C), pages 46-58.
    10. Gössling, Stefan & Humpe, Andreas & Hologa, Rafael & Riach, Nils & Freytag, Tim, 2022. "Parking violations as an economic gamble for public space," Transport Policy, Elsevier, vol. 116(C), pages 248-257.
    11. Luetian Sun & Rui Song, 2022. "Improving Efficiency in Congested Traffic Networks: Pareto-Improving Reservations through Agent-Based Timetabling," Sustainability, MDPI, vol. 14(4), pages 1-24, February.
    12. Rodríguez-Martín, Inmaculada & Yaman, Hande, 2022. "Periodic Vehicle Routing Problem with Driver Consistency and service time optimization," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 468-484.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:4145-:d:1395167. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.