Parking Data Analysis and Model Optimization Based on SF Park Project

With the rapid development of economy and the improvement of people’s living standard, the car ownership is increasing. The phenomenon of “parking difficulty” and “parking disorder” caused by the supply of urban parking facilities is becoming more and more serious. Parking price is an effective parking management measure to adjust parking demand distribution. This study is based on the implementation data of regional time-varying parking price obtained from the SF Park project in San Francisco, U.S. The collected data include the price adjustment range and parking space utilization. It can analyze the sensitivity of different of regional travelers to the fluctuation of parking price. The regression analysis method based on panel data is used to study the impact of parking price changes on parking occupancy in a certain period. Finally, by establishing an optimization model, the optimal parking price change and the scheme of parking space utilization are obtained. The study finds that parking price changes have different regulating effects on parking demand in different regions. The optimization model established has better effect. The conclusions can provide a reference for regional parking pricing and reduce parking problems.


  • English

Media Info

  • Media Type: Web
  • Pagination: pp 3658-3669
  • Monograph Title: CICTP 2020: Transportation Evolution Impacting Future Mobility

Subject/Index Terms

Filing Info

  • Accession Number: 01768399
  • Record Type: Publication
  • ISBN: 9780784483053
  • Files: TRIS, ASCE
  • Created Date: Dec 9 2020 3:05PM