Inventory of private parking spaces: Approaches to estimating the supply of off-street parking spaces in residential areas
Laura Merten & Tobias Kuhnimhof
What the paper says
Data on private, off-street parking infrastructure are scarce, as the data are generally not systematically collected by public institutions and difficult to survey due to often inaccessible locations. As data are needed for targeted parking policies and for research related to parking, good estimates are required. Although such estimations are used in several studies, no study has yet compared different estimation approaches or evaluated their accuracy. Based on a literature review, we develop four approaches to estimating residential private parking supply and apply them to the city of Aachen, Germany. By comparing the estimates to a manually conducted survey in diverse neighborhoods, we evaluate and discuss the accuracy of the approaches. Our results highlight the difficulty of obtaining reliable data on private parking spaces, as the estimates vary considerably. Among the tested approaches, the application of a binary logit model based on real estate data provides the closest match to the surveyed parking supply. As this approach is capable of accounting for the large spatial variety in parking space availability within a city, it is not only suitable for city-wide estimations, but also for estimating the residential private parking supply in smaller spatial units like city blocks.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.