Discrete-Time Hazard Model of the Dynamic Utilization of Parking Spaces within Park-and-Ride Lots

Abstract

Park-and-ride (P&R) offers an alternative to the exclusive use of the car when considering the door-to-door travel experience. The intended effects of good P&R services are an increase in public transport ridership, a decrease in the vehicle-kilometers traveled, and a reduction in the number of cars in the city centers. However, no consensus exists in the literature about the effectiveness of P&R, and no consideration of parking space utilization exists when searching for the optimal location of P&R lots or analyzing P&R choices. Accordingly, this study models the utilization of 7590 parking spaces in 20 P&R lots along the major arterials around Brisbane (Australia). A discrete-time logistic regression model calculates the probability that each parking space is occupied at the end of one of 60 time intervals between 4:00 a.m. and 9:00 a.m. on a weekday. The findings from the model suggest that the probability of a parking space to be occupied increases with a larger capacity of the P&R lot, a larger number of public transport services, and a lower walking time to the platforms. Moreover, the results suggest that a parking space is more likely to be occupied in P&R lots farther from the central business district (CBD) until 8.00 a.m., but it is more probable to be occupied in P&R lots closer to the CBD from 8.00 a.m. onwards. This dynamic model of parking space utilization within a P&R lot could contribute to the evaluation of future P&R utilization, the formulation of realistic optimization models, and the estimation of dynamic activity-based models.