Improving Parking Availability Maps using Information from Nearby Roads

authored by
Fabian Bock, Monika Sester
Abstract

Parking search traffic causes increased travel times and air pollution in many cities. Real-time parking availability maps are expected to help drivers to find a parking space faster and thus to reduce parking search traffic. A possibility to create such maps is the aggregation of parking availability information from crowdsourcing solutions like probe vehicles and mobile phone applications. Since these sources cannot sense the whole city at the same time, estimation methods are necessary to fill uncovered areas. This paper investigates the estimation of parking availability based on spatial methods using sensor data from San Francisco. First, spatial similarities in parking availability are evaluated for different aspects like time of day and number of parking spaces depending on the distance to reveal the parking characteristics. Then, interpolation methods are examined to estimate parking availability in unobserved road segments. Results show that relevant similarities mainly exist for short distances of less than hundred meters. Their similarity values are lower than the temporal similarity even for multiple hours of time gap. Nevertheless, spatial information is useful to interpolate parking availability. Investigated interpolation methods show significantly better results than random guess. Inverse distance weighting method outperforms a simple averaging by up to 5%.

Organisation(s)
Institute of Cartography and Geoinformatics
Type
Article
Journal
Transportation Research Procedia
Volume
19
Pages
207-214
No. of pages
8
ISSN
2352-1457
Publication date
28.12.2016
Publication status
Published
Peer reviewed
Yes
ASJC Scopus subject areas
Transportation
Sustainable Development Goals
SDG 11 - Sustainable Cities and Communities
Electronic version(s)
https://doi.org/10.1016/j.trpro.2016.12.081 (Access: Open)
https://doi.org/10.15488/1656 (Access: Open)