Identifying Feasible Locations for Rail Transit Stations

Abstract

A public transportation system is a viable alternative to reducing traffic congestion and environmental pollution in urban areas. A metro, subway, or light rail system may be a viable commuting alternative connected with a coordinated service of feeder buses in urban and suburban neighborhoods. The decision to build a rail transit system is largely driven by available land and feasible sites for tracks and stations. Factors like ridership and public perception are considered in identifying suitable rail corridor and station locations. A two-stage analytical model is developed for identifying feasible rail transit station sites based on the real geographical and demographic data. The model uses a genetic algorithm (GA) for optimally locating the stations and works in parallel with a geographical information system (GIS). The model is applied in an example by using real GIS data, road network, and demographic information. The potential station sites are identified in the first stage, and the optimization using the GA is performed in the second stage by minimizing the total cost of locating the stations.