Park-and-ride facility location optimization: A case study for Nashville, Tennessee

Abstract

Strategic placement of park-and-ride (P&R) facilities is important to ensure the facilities are effectively utilized by commuters, avoiding oversubscription or underutilization after placement. This study develops a framework that integrates a demand model and an optimization model to study the optimal placement of P&R facilities to maximize the total number of commuters who switch from single occupancy vehicles to public transit. The framework first develops a P&R demand model through a discrete choice model, specifically the multinomial logit model, to characterize the mode choice behavior of individuals in a multimodal network. Next, it leverages the estimated proportion of commuters that are expected to switch to P&Rs from alternatives in a mixed integer linear programming optimization model to prescribe the optimal locations of P&R facilities. This study also accounts for practical considerations and introduces an approach to estimate the potentially unknown demand for P&R facilities. The framework is applied through a case study for the City of Nashville, a major metropolitan area in the State of Tennessee, US. Model calibration is performed using the literature and available data at Nashville. The results of the case study are then presented and sensitivity analysis is performed to provide further insights. The results of the case study suggest that the optimal placement of P&R facilities has the potential to improve the network performance, and reduce emission and vehicle kilometer traveled.