Models and Solution Algorithms for Transit and Intermodal Passenger Assignment (Development of FAST-TrIPs Model)

In this study, a comprehensive set of transit, intermodal and multimodal assignment models (FAST-TrIPs) is developed for transportation planning and operations purposes. The core part of the models is a schedule-based transit assignment with capacity constraint and boarding priority. The problem is defined to model the system performance dynamically by taking into account the scheduled transit service and to model user behavior more realistically by taking into account capacity of transit vehicles and boarding priority for passengers arriving early to a stop or a transfer point. An optimization model is proposed for both deterministic and stochastic models, which includes a penalty term in the objective function to model the boarding priority constraint. The stochastic model is proposed based on logit route choice with flexibility on the level of stochasticity in route choice. Optimality conditions show that the models are consistent with network equilibrium and user behavior. An extension of the optimization models is proposed for multimodal assignment problem, in which the transit and auto networks interact dynamically. To solve the proposed models, since the penalty term is non-linear and makes the model an asymmetric nonlinear optimization model with side constraints, a simulationbased approach is developed. The solution method incorporates the path assignment models and a mesoscopic transit passenger simulation in conjunction with Dynamic Traffic Assignment (DTA) models. The simulation model can capture detailed activities of transit passengers and determines the nonlinear penalty explicitly by reporting 1 FAST-TrIPs: Flexible Assignment and Simulation Tool for Transit and Intermodal Passengers