Abstract
Parking Guidance and Information (PGI) solutions are a well-known class of Intelligent Transportation Systems meant to support drivers by recommending locations and routes with higher chance to find parking. However, the relevance of such systems for on-street parking spaces is barely studied. In this paper, we investigate the consequences of providing the drivers with different parking information to the search. Based on real-world parking data from San Francisco, we investigated the scenario in which a driver does not find a parking space at the destination and has to decide on the next road to go. We consider three different scenarios: (I) No parking availability information; (II) static information about the capacity of a road segment and temporary parking limitations; (III) real-time information collected from stationary sensors. Clearly the latter has strong implications in terms of deployment and operational costs. These scenarios lead to three different guidance strategies for a PGI system. The empirical experiments we conducted on real on-street parking data from San Francisco show that there is a significant reduction of parking search with more informed strategies, and that the use of real-time information offers only a limited improvement over static one.
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Notes
- 1.
In the following we will identify with the term road segment the part of a road between two subsequent intersections.
- 2.
Please note that we neglect walking distances in this consideration.
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Acknowledgment
This research has been supported by the German Research Foundation (DFG) through the Research Training Group SocialCars (GRK 1931). The focus of the SocialCars Research Training Group is on significantly improving the city’s future road traffic, through cooperative approaches. This support is gratefully acknowledged.
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Bock, F., Di Martino, S., Sester, M. (2019). What Is the Impact of On-street Parking Information for Drivers?. In: Kawai, Y., Storandt, S., Sumiya, K. (eds) Web and Wireless Geographical Information Systems. W2GIS 2019. Lecture Notes in Computer Science(), vol 11474. Springer, Cham. https://doi.org/10.1007/978-3-030-17246-6_7
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