Optimal Management of Shared Parking Spaces under Uncertain Supply and Demand: An Agent-Based Approach

Shared parking has the potential to alleviate urban parking headaches through improving utilization of the existing parking resources. Especially in residential zones where residents with vehicles have a high risk of not finding parking upon their return home. Based on the precondition that all residents have a parking space, the objective of this paper is to explore the potential of shared parking spaces. Firstly, a reservation and allocation mechanism for shared parking was proposed. Secondly, an agent simulation model was developed to track the NP-hard problem, regarding the shared procedure as a queuing system. Finally, the optimal number of shared parking spaces was obtained through numerical tests. The results prove that the proposed shared strategy offers significant improvements in utilization and turnover rate of parking spaces, compared to the non-shared circumstances. This paper provides a novel method which contributes to managing the high demand for parking spaces in urban areas.

• Record URL:
  • https://doi.org/10.1061/9780784483053.241
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784483053
• Supplemental Notes:
  • © 2020 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Zhao, Pengfei
  • Guan, Hongzhi
• Conference:
  • 20th COTA International Conference of Transportation Professionals
  • Location: Xi’an , China
  • Date: 2020-8-14 to 2020-8-16
• Publication Date: 2020

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 2864-2871
• Monograph Title: CICTP 2020: Transportation Evolution Impacting Future Mobility

Subject/Index Terms

• TRT Terms: Parking demand; Parking facilities; Residential areas; Resource allocation; Shared parking; Urban areas
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01768195
• Record Type: Publication
• ISBN: 9780784483053
• Files: TRIS, ASCE
• Created Date: Mar 25 2021 9:35AM