Dynamic pricing and reservation for intelligent urban parking management

Chao Lei, Yanfeng Ouyang

Research output: Contribution to journalArticlepeer-review


Despite rapid advances of information technologies for intelligent parking systems, it remains a challenge to optimally manage limited parking resources in busy urban neighborhoods. In this paper, we use dynamic location-dependent parking pricing and reservation to improve system-wide performance of an intelligent parking system. With this system, the parking agency is able to decide the spatial and temporal distribution of parking prices to achieve a variety of objectives, while drivers with different origins and destinations compete for limited parking spaces via online reservation. We develop a multi-period non-cooperative bi-level model to capture the complex interactions among the parking agency and multiple drivers, as well as a non-myopic approximate dynamic programming (ADP) approach to solve the model. It is shown with numerical examples that the ADP-based pricing policy consistently outperforms alternative policies in achieving greater performance of the parking system, and shows reliability in handling the spatial and temporal variations in parking demand.

Original languageEnglish (US)
Pages (from-to)226-244
Number of pages19
JournalTransportation Research Part C: Emerging Technologies
StatePublished - Apr 1 2017


  • Approximate dynamic programming
  • Dynamic pricing
  • Equilibrium
  • MPEC
  • Parking management

ASJC Scopus subject areas

  • Transportation
  • Automotive Engineering
  • Civil and Structural Engineering
  • Management Science and Operations Research


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