Framework and Model for Parking Decisions
Ofir Hilvert, Tomer Toledo, Shlomo Bekhor
Abstract
Ofir Hilvert, Tomer Toledo, Shlomo Bekhor
Abstract
The search for available parking is one of the most challenging consequences of global urbanization and growth in motorization. This paper presents an overall framework for parking choice and search behavior, composed of three time–space phases: (a) pretrip static decision; (b) en route, passive search; and (c) in-area search strategy adaptation. The empirical part of the paper focuses on the first phase and describes a parking choice model that is based on pooled stated and revealed preference data sources. A special, web-based survey was designed to model the choice of parking type (on-street versus off-street parking). The model estimation results showed that the choice of parking location was affected by parking cost, search time, and walk time to the destination, facility type, and decision-maker characteristics. The model was applied to a case study to illustrate its capabilities to evaluate various policy measures. Specifically, the effect of a change in the demand for on- and off-street parking was evaluated with respect to the parking pricing policy and the value of search time for various parking durations.
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The search for available parking is one of the most challenging consequences of global urbanization and growth in motorization. This paper presents an overall framework for parking choice and search behavior, composed of three time–space phases: (a) pretrip static decision; (b) en route, passive search; and (c) in-area search strategy adaptation. The empirical part of the paper focuses on the first phase and describes a parking choice model that is based on pooled stated and revealed preference data sources. A special, web-based survey was designed to model the choice of parking type (on-street versus off-street parking). The model estimation results showed that the choice of parking location was affected by parking cost, search time, and walk time to the destination, facility type, and decision-maker characteristics. The model was applied to a case study to illustrate its capabilities to evaluate various policy measures. Specifically, the effect of a change in the demand for on- and off-street parking was evaluated with respect to the parking pricing policy and the value of search time for various parking durations.
Key concepts: Parking guidance and information, Revealed preference, Computer science, Preference, Transport engineering, Parking space, Travel time, Operations research