Year: 2019
Type: dissertation
Study design: Observational Study
Abstract: This study develops a stated preference survey, named iCity Park, as a parking simulation game to collect drivers’ on-street parking choices when legal and illegal parking spots are available, and parking enforcement is present. The gamification incentive and simulated hypothetical scenarios in the survey are proven to be effective for high-quality data. iCity Park also simulates parking activities with and without ITS assistance. This study develops three types of logit models for the two assistance levels. The estimated mixed logit models have the best goodness of fit and demonstrate the significance of respondents’ parking preference heterogeneity. Then models for the two assistance levels are compared, and the influential power of the explanatory variables are analyzed. This thesis contributes to innovative data collection methods and provides a better understanding of parking choice process and parking behavioural changes with the assistance of parking information systems.
Source: TSpace (University of Toronto)
Author: Bo Wang
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3090045889