Improving train service reliability by applying an effective timetable robustness strategy

ABSTRACT

To avoid propagation of delays in dense railway timetables, it is important to ensure robustness. One strategy to improve robustness is to provide adequate amount of buffer times between trains. This study concerns how “scheduled minimum headways” should be determined in order to improve robustness in timetables. Scheduled minimum headways include technical minimum headway plus some buffer time. We propose a strategy to be implemented in timetables at the final stages of planning and prior to the operations. The main contributions of this study are 1) to propose a strategy where the size of the scheduled minimum headways is dependent on trains' travel times instead of a fixed-sized time slot and it is called “travel time dependent scheduled minimum headways” or TTDSMH, 2) to evaluate the effects of the new strategy on heterogeneity, speed, and the number of trains in timetables, 3) to show that a simple strategy can improve robustness without imposing major changes in timetables. The strategy is implemented in an Mixed Integer Linear Programming framework for timetabling and tested for some problem instances from Sweden. Results show that TTDSMH can improve robustness. The proposed strategy can be applied in intelligent transportation tools for railway timetabling.     

Frequency-based transit assignment considering seat capacities

This paper proposes a frequency-based assignment model that considers travellers probability of finding a seat in their perception of route cost and hence also their route choice. The model introduces a “fail-to-sit” probability at boarding points with travel costs based on the likelihood of travelling seated or standing. Priority rules are considered; in particular it is assumed that standing on-board passengers will occupy any available seats of alighting passengers before newly boarding passengers can fill any remaining seats. At the boarding point passengers are assumed to mingle, meaning that FIFO is not observed, as is the case for many crowded bus and metro stops, particularly in European countries. The route choice considers the common lines problem and an user equilibrium solution is sought through a Markov type network loading process and the method of successive averages. The model is first illustrated with a small example network before being applied to the inner zone of London’s underground network. The effect of different values passengers might attach to finding a seat are illustrated. Applications of the model for transit planning as well as for information provision at the journey planner stage are discussed.     

Passenger arrival and waiting time distributions dependent on train service frequency and station characteristics: A smart card data analysis

Waiting time at public transport stops is perceived by passengers to be more onerous than in-vehicle time, hence it strongly influences the attractiveness and use of public transport. Transport models traditionally assume that average waiting times are half the service headway by assuming random passenger arrivals. However, research agree that two distinct passenger behaviour types exist: one group arrives randomly, whereas another group actively tries to minimise their waiting time by arriving in a timely manner at the scheduled departure time. This study proposes a general framework for estimating passenger waiting times which incorporates the arrival patterns of these two groups explicitly, namely by using a mixture distribution consisting of a uniform and a beta distribution. The framework is empirically validated using a large-scale automatic fare collection system from the Greater Copenhagen Area covering metro, suburban, and regional rail stations thereby giving a range of service headways from 2 to 60 min. It was shown that the proposed mixture distribution is superior to other distributions proposed in the literature. This can improve waiting time estimations in public transport models. The results show that even at 5-min headways 43% of passengers arrive in a timely manner to stations when timetables are available. The results bear important policy implications in terms of providing actual timetables, even at high service frequencies, in order for passengers to be able to minimise their waiting times.