Details
| Original language | English |
|---|---|
| Title of host publication | Web and Wireless Geographical Information Systems |
| Subtitle of host publication | 17th International Symposium, W2GIS 2019, Kyoto, Japan, May 16–17, 2019, Proceedings |
| Editors | Yukiko Kawai, Sabine Storandt, Kazutoshi Sumiya |
| Publisher | Springer Verlag |
| Pages | 75-84 |
| Number of pages | 10 |
| Edition | 1. |
| ISBN (electronic) | 978-3-030-17246-6 |
| ISBN (print) | 978-3-030-17245-9 |
| Publication status | Published - 10 Apr 2019 |
| Event | 17th International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2019 - Kyoto, Japan Duration: 16 May 2019 → 17 May 2019 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 11474 |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
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.
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
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Web and Wireless Geographical Information Systems: 17th International Symposium, W2GIS 2019, Kyoto, Japan, May 16–17, 2019, Proceedings. ed. / Yukiko Kawai; Sabine Storandt; Kazutoshi Sumiya. 1. ed. Springer Verlag, 2019. p. 75-84 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11474).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - What Is the Impact of On-street Parking Information for Drivers?
AU - Bock, Fabian
AU - Di Martino, Sergio
AU - Sester, Monika
N1 - Funding information: 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.
PY - 2019/4/10
Y1 - 2019/4/10
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85065992358&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-17246-6_7
DO - 10.1007/978-3-030-17246-6_7
M3 - Conference contribution
AN - SCOPUS:85065992358
SN - 978-3-030-17245-9
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 75
EP - 84
BT - Web and Wireless Geographical Information Systems
A2 - Kawai, Yukiko
A2 - Storandt, Sabine
A2 - Sumiya, Kazutoshi
PB - Springer Verlag
T2 - 17th International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2019
Y2 - 16 May 2019 through 17 May 2019
ER -