Investigating the Influence of On-Street Parking Guidance Strategies on Urban Mobility

verfasst von

Sergio Di Martino, Vincenzo Norman Vitale, Urs Fabian Bock

Abstract

Parking Guidance and Information (PGI) solutions are a type of Intelligent Transportation System aimed at helping drivers by suggesting routes leading to facilities with higher parking availability. Current PGIs are mainly limited to multi-storey car parks, where this availability information can be easily collected. On the other hand, monitoring on-street parking availability is a challenge, requiring very expensive sensor deployments. The actual benefits of such investments to provide up-To-date on-street parking availability data for PGIs has been barely studied.To fill this gap, in this paper, we present the results of an investigation on the influence of three different types of on-street parking information on urban mobility. Based on real on-street parking data from San Francisco (USA), we investigated the scenario where a PGI has to support a driver who has not found an on-street parking space at his/her destination, and has to decide on the next road to go. We compared four scenarios for the PGI guidance, based on: (I) actual parking availability information, collected from stationary sensors, (II) static information about the parking capacity of a road segment and (temporary) parking limitations, (III) static information about only parking limitations, and (IV) no information at all. Clearly these solutions have strong implications in terms of deployment and operational costs. Results show that there is a significant reduction of parking search with more informed strategies, but also that the use of real-Time information makes sense only presence of limited parking availabilities. Indeed, whenever the parking dynamics are not very competitive, real-Time data offers only a limited improvement over static one.

Organisationseinheit(en)

Institut für Kartographie und Geoinformatik

Externe Organisation(en)

Università degli Studi di Napoli Federico II

Typ

Aufsatz in Konferenzband

Anzahl der Seiten

6

Publikationsdatum

06.2019

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Verkehr, Artificial intelligence, Fahrzeugbau, Modellierung und Simulation

Ziele für nachhaltige Entwicklung

SDG 11 – Nachhaltige Städte und Gemeinschaften

Elektronische Version(en)

https://doi.org/10.1109/MTITS.2019.8883367 (Zugang: Geschlossen)