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.
What Is the Impact of On-street Parking Information for Drivers? / Bock, Fabian; Di Martino, Sergio; Sester, Monika. - 11474:(2019), pp. 75-84. (Intervento presentato al convegno 17th International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2019 tenutosi a Giappone nel 2019) [10.1007/978-3-030-17246-6_7].
What Is the Impact of On-street Parking Information for Drivers?
Di Martino, Sergio
;
2019
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.