A STOCHASTIC TRANSIT ASSIGNMENT MODEL USING A DYNAMIC SCHEDULE-BASED NETWORK
operations - scheduling, ridership - commuting, ridership - demand, mode - rail
Travel models (Travel demand), Travel demand, Timetables, Stochastic processes, Scheduling, Random processes, Railways, Railroads, Passenger demand, Headways, Algorithms
Using the schedule-based approach, in which scheduled time-tables are used to describe the movement of vehicles, a dynamic transit assignment model is formulated. Passengers are assumed to travel on a path with minimum generalized cost which consists of four components: in-vehicle time; waiting time; walking time; and a time penalty for each line change. With the exception of in-vehicle time, each of the other cost components is weighted by a sensitivity coefficient which varies among travelers and is defined by a density function. This time-dependent and stochastic minimum path is generated by a specially developed branch and bound algorithm. The assignment procedure is conducted over a period in which both passenger demand and train headways are varying. Due to the stochastic nature of the assignment problem, a Monte Carlo approach is employed to solve the problem. A case study using the Mass Transit Railway System in Hong Kong is given to demonstrate the model and its potential applications.
Tong, C, Wong, S, (1999). A STOCHASTIC TRANSIT ASSIGNMENT MODEL USING A DYNAMIC SCHEDULE-BASED NETWORK. Transportation Research Part B: Methodological, Volume 33, Issue 2, p. 107-121.