Optimizing location and capacity of rail-based Park-and-Ride sites to increase public transport usage

This paper presents a new methodology to identify optimal locations and capacity for rail-based Park-and-Ride (P&R) sites to increase public transport mode share. P&R is usually taken as an important component of policies for the sustainable development of urban transport systems. However, previous studies reveal that arbitrarily determined P&R sites may act to reduce public transport commuting. This paper proposes a methodology for the optimal location and capacity design of P&R sites, with the aim of enhancing public transport usage. A Combined Mode Split and Traffic Assignment (CMSTA) model is proposed for the P&R scheme. Taking the CMSTA model as the lower level, a bi-level mathematical programming model is then built to establish the optimal location and capacity of P&R sites. A heuristic genetic algorithm is adopted to solve this model. Finally, a network example is adopted to test numerically the proposed models and algorithms.