A Conceptual Framework for Forecasting Car Driver’s On-Street Parking Decisions

Abstract

This paper describes a conceptual framework of a behavioral model, well able to predict the parking choice decision process of car drivers’ while driving in a city center. The model assumes that parking choice decisions are mainly based on features associated to road conditions that a car driver faces while entering a street. A stated preference experiment was designed to collect respondents’ preferences related to preferred parking facility. A set of hypothetical road conditions were presented in the form of choice tasks. The collected data is analyzed using mixed multinomial logit model. The results from the model estimation show that almost all the presented attributes such as parking costs, payment options, expected parking duration, speed limit, level of parking convenience, space availability and surrounding activities play a considerable role when determining car drivers’ parking preferences. Moreover, the model highlights relatively important road related attributes which can induce search traffic. Therefore, cruising for parking can be reduced by avoiding certain road conditions, this information is valuable for the local authorities to design efficient parking policies.