An Advanced Parking Navigation System for Downtown Parking

Zhibin Chen (), Stephen Spana, Yafeng Yin and Yuchuan Du
Additional contact information
Zhibin Chen: University of Michigan
Stephen Spana: University of Florida
Yafeng Yin: University of Michigan
Yuchuan Du: Tongji University

Networks and Spatial Economics, 2019, vol. 19, issue 3, No 12, 953-968

Abstract: Abstract This paper develops a novel parking navigation system for downtown parking that aims to mitigate parking competition by guiding drivers to appropriate vacant parking spaces. Given drivers’ real-time locations and their parking preferences, a two-sided matching algorithm is firstly adopted to achieve a stable driver-optimal matching, under which drivers will be assigned to their most appropriate parking spaces (if any), and have no incentive to misreport their private information (e.g., parking space preferences). Although drivers’ private information is required for the navigation system, a distributed solution procedure is applied to achieve the space assignment without disclosing such information. Lastly, simulation experiments are conducted to demonstrate the capability of the proposed navigation system on reducing driving time and the frequency of changed navigation compared with other navigation systems.

Keywords: Parking navigation; Two-sided match; Driver-optimal matching; Distributed stable match (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s11067-019-9443-4

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