The use of fossil fuels in transportation generates harmful emissions that accounts for nearly half of the total pollutants in urban areas. Dealingwith this issue, local authorities are dedicating specific efforts to seize the opportunity offered by new fuels and technological innovations in achieving a cleaner urban mobility. In fact, authorities are improving environmental performances of their public transport fleet by procuring cleaner vehicles, usually called low and zero emission vehicles (LEV and ZEV, respectively). Nevertheless there seems to be a lack of methodologies for supporting stakeholders in decisions related to the introduction of green vehicles, whose allocation should be performed since the network design process in order to optimize their available green capacity. In this paper, the problem of clean vehicle allocation in an existing public fleet is facedby introducing a method for solving the transit network design problem ina multimodal, demand elastic urban context dealing with the impacts deriving from transportation emissions. The solving procedure consists of a setof heuristics which includes a routine for route generation and a geneticalgorithm for finding a sub-optimal set of routes with the associated frequencies. (A) Reprinted with permission from Elsevier.
Abstract