A spatially disaggregated model for the technology selection and design of a transit line

Our research question is the usefulness of a high level of spatial granularity for the travel demand when planning a transit line. We formulate a new optimization model for the technology selection and design of a transit line where the spatial attributes of the travel demand can be finely set. The solution method relies on approximated formulae, and we establish relationships with a classic result for the optimal stop spacing. We also present a refinement of the in-vehicle passenger crowding for an existing transit design model where demand spatial attributes are set synthetically. We call spatially disaggregate and spatially aggregate the former and the latter model, respectively. These two models are compared by numerical experiments on a scenario for three semi-rapid transit technologies where two variants consider opposite demand profiles in terms of spatial distribution. We conclude that the spatially aggregated model is sufficient when the main goal is technology selection, whereas the spatially disaggregate model is better for design and benchmarking purposes.