Rail Transit Route Optimization Model for Rail Infrastructure Planning and Design: Case Study of Saint Andrews, Scotland
mode - rail, place - europe, technology - geographic information systems, land use - impacts, planning - environmental impact, planning - route design, infrastructure - station, economics - appraisal/evaluation
Route optimization, Rail infrastructure planning, Genetic algorithms, GIS
This paper is aimed at developing a rail transit route optimization model (RTROM) for cost-effective and sustainable rail infrastructure planning and design. Locations of rail transit routes and stations depend on many factors, including potential ridership, costs of land, construction and operation, land use, connecting routes, passenger travel times, and environmental impacts. Suitably located rail transit routes effectively serve the potential demand while also minimizing costs and environmental impacts. Thus, a common problem in all rail infrastructure planning and design projects is to identify the best possible route that satisfies design constraints (such as minimum radius, maximum gradient, and vertical clearance), geographical considerations (such as demand generators and socio-economically sensitive areas) and objectives (such as minimization of associated costs and environmental impacts, or maximization of net benefits). The developed RTROM uses a genetic algorithm for performing optimization, which is integrated to a geographic information system for seamless transfer of land-use, environmental, and topographic data during the optimal search process. The model is tested in a real-world case study from Saint Andrews, Scotland. The lessons learned from the real-world application of the model are discussed. Many extensions of the model remain to be tested in future works.
Read More: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29TE.1943-5436.0000445
Kang, M., Jha, M., and Buddharaju, R. (2014). Rail Transit Route Optimization Model for Rail Infrastructure Planning and Design: Case Study of Saint Andrews, Scotland. Journal of Transportation Engineering, Vol. 140, No.1, pp. 1–11.