Optimal Guidance Algorithms for Parking Search with Reservations

Michael W. Levin, Stephen D. Boyles

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


To alleviate the congestion caused by searching for parking, internet- or smartphone-based parking reservation systems have been deployed in major cities. We develop algorithms to provide optimal guidance to individual drivers on where to search for or reserve parking and how to navigate the traffic while searching for parking, a problem which has yet to be addressed in the literature. Drivers holding a reservation pay a holding cost per unit time until they park, so it is often suboptimal to reserve parking before departing. We formulate a Markov decision process to decide both where to attempt to reserve parking and which route to take. The optimal parking space to reserve changes as the driver travels through the network. Results on the downtown Austin network show that reserving parking affects route choice and reduces cruising for parking compared to not reserving parking. Our model and solution algorithm could be integrated with GPS navigation systems to provide guidance to individual drivers on optimal navigation and use of parking reservation systems.

Original languageEnglish (US)
Pages (from-to)19-45
Number of pages27
JournalNetworks and Spatial Economics
Issue number1
StatePublished - Mar 1 2020

Bibliographical note

Funding Information:
The authors gratefully acknowledge Dr. Tarun Rambha?s comments and suggestions. The authors also appreciate the support of the Data-Supported Transportation Operations & Planning Center and the National Science Foundation, Grant No. 1254921.

Publisher Copyright:
© 2019, Springer Science+Business Media, LLC, part of Springer Nature.


  • Markov decision process
  • Online shortest path
  • Parking reservation search


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