A continuous approximation model for the design of park-and-ride systems

Abstract

Park-and-Ride (P&R) systems have emerged as a popular traffic management solution in response to the need for sustainable transportation options to combat the climate crisis and improve traffic flow. The goal of this research is to foster the use of public transportation by facilitating the design of P&R through sketch planning tools. This research aims to (1) formulate mathematical models to optimize the selection of P&R design variables, (2) analyze the effects of local conditions of land use and traffic on design variables of P&R, (3) analyze the influence of key features (location, transit service level, fares, etc.) on the expected demand and benefits. The models consider a continuous metropolitan area with population distribution defined by density functions. The number of P&R users are estimated through an analytical formulation of the catchment area of a P&R site and mode choice functions that take into the generalized travel costs of using P&R or driving-only. The mathematical models maximize expected user benefit and can be used to select P&R location and design the public transportation servicing the site. Numerical experiments are conducted to provide valuable insights into the implementation of P&R systems and offer guidelines for future design and planning efforts.