|M.Sc Student||Hilvert Ofir|
|Subject||Models of Parking Search Behavior|
|Department||Department of Civil and Environmental Engineering||Supervisors||Professor Tomer Toledo|
|Professor Shlomo Bekhor|
|Full Thesis text|
The parking problem is one of the most challenging symptoms resulting from the global urbanization and motorization growth. Parking policies play a central part in the effort to tackle the parking problem. One of the strategic tools for policies evaluation are the disaggregative choice models, which can simulate, predict and point out driver's parking choice and preferences. This study presents a parking choice model estimated on the basis of pooled stated and revealed preference data sources. The preference data collection method included the administration of a web-based survey. The survey consisted of three parts, revealed preference section regarding respondent's last or most frequent trip, a stated preference section introducing nine hypothetical choice questions, and a socio-demographic section. It was distributed around Technion's students and the general population. In addition, a parking search behavior framework was introduced. The framework consisted of three time-space phases: pre-trip static decision, en-route passive search, and in-area search strategy adaptation. The parking model was applied to a parking scenario in order to demonstrate the model capabilities in evaluating various policy measures. The application compared the effects of various parking policies (represented as a shift from the current parking conditions) on drivers' parking choices. Additionally, walking and searching time values were calculated in order to reflect parking related time saving values. Results imply that the most influential factor of the static parking decision is the parking price. Thus, pricing policies promise the best potential results in affecting drivers' parking decisions .