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Optimal Guidance Algorithms for Parking Search with Reservations

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Abstract

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.

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Acknowledgements

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.

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  1. Department of Civil, Environmental, and Geo- Engineering, University of Minnesota, 140 Civil Engineering Building, 500 Pillsbury Drive SE, Minneapolis, MN, 55455, USA

    Michael W. Levin

  2. Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, Ernest Cockrell, Jr. Hall (ECJ) 6.204, 301 E. Dean Keeton St. Stop C1761, Austin, TX, 78712-1172, USA

    Stephen D. Boyles

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Correspondence to Michael W. Levin.

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Levin, M.W., Boyles, S.D. Optimal Guidance Algorithms for Parking Search with Reservations. Netw Spat Econ 20, 19–45 (2020). https://doi.org/10.1007/s11067-019-09464-7

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