A Stochastic Process Approach for Frequency-based Transit Assignment with Strict Capacity Constraints.

Teklu, Fitsum

Transit assignment models represent the stochastic nature of waiting times, but usually adopt a deterministic representation route flows and costs. Especially in cities where transit vehicles are small and not operating to timetables, there is a need to represent the variability in flows and costs to enable planners make more informed decisions. Stochastic process (SP) models consider the day-to-day dynamics of the transit demand-supply system, explicitly modelling passengers’ information acquisition and decision processes. A Monte Carlo simulation based SP model that includes strict capacity constraints is presented in this paper. It uses micro-simulation to constrain passenger flows to capacities and obtain realistic cost estimates. Applications of the model and its comparison with the De Cea and Fernandez ( Transp Sci, 27:133–147, ) model are presented using a small network.

LOCAL transit access; STOCHASTIC processes; TRANSPORTATION; SUPPLY & demand; COST estimates; PROBABILITY theory; MONTE Carlo method; NUMERICAL calculations; TIME perspective

Networks & Spatial Economics, 2008, Vol 8, Issue 2/3, p225

1566-113X

Academic Journal

10.1007/s11067-007-9046-3