PREDICTING ON-TIME PERFORMANCE IN SCHEDULED RAILROAD OPERATIONS: METHODOLOGY AND APPLICATION TO TRAIN SCHEDULING
operations - scheduling, operations - performance, planning - route design, planning - signage/information, organisation - performance, mode - rail
Train operation, Train handling, Stochastic processes, Random processes, Railways, Railroads, Monte Carlo method, Line haul transport, Line haul, Dynamic route guidance, Computer aided routing system, Advanced driver information systems, Advanced driver information systems, ADIS
In previous work, the authors developed an analytical line delay model for analyzing rail line-haul operations, and validated the model as a predictive tool. This paper examines the application of the model as a prescriptive tool for the generation of train schedules. A unique feature of the model is that it incorporates dynamic meet/pass priorities in order to approximate an optimal meet/pass planning process. Extensive Monte Carlo simulations are conducted to examine the application of the model for adjusting real-world schedules to improve on-time performance and reduce delay. This empirical work represents the first attempt to investigate the impacts of the scheduling methodology on on-time line-haul performance. The problems are based on historical data from a major North American railroad.
Hallowell, S, Harker, P, (1998). PREDICTING ON-TIME PERFORMANCE IN SCHEDULED RAILROAD OPERATIONS: METHODOLOGY AND APPLICATION TO TRAIN SCHEDULING. Transportation Research Part A: Policy and Practice, Volume 32, Issue 4, p. 279-295.