Timetabling for Strategic Passenger Railway Planning

Abstract

In research and practice, public transportation planning is executed in a series of steps, which are often divided into the strategic, the tactical, and the operational planning phase. Timetables are normally designed in the tactical phase, taking into account a given line plan, safety restrictions arising from infrastructural constraints, as well as regularity requirements and bounds on transfer times. In this paper, however, we propose a timetabling approach that is aimed at decision making in the strategic phase of public transportation planning and to determine an outline of a timetable that is good from the passengers' perspective. Instead of including explicit synchronization constraints between train runs (as most timetabling models do), we include the adaption time (waiting time at the origin station) in the objective function to ensure regular connections between passengers' origins and destinations. We model the problem as a mixed integer quadratic program and linearise it. Furthermore we propose a heuristic to generate starting solutions. We illustrate the type of solutions found by our approach on two case studies based on the Dutch railway network and analyse trade-offs that are made to balance dwell times and regularity of trains.

An Iterative Heuristic for Passenger-Centric Train Timetabling with Integrated Adaption Times

“…While the model allows to group passengers into (predefined) time slices and penalize deviation from the respective time slice, a heuristic to including adaption time, in the numerical experiments reported in Gattermann et al [2016] however, only one time slice (that spans the whole period) is used. Polinder et al [2020] consider timetabling in the strategic railway planning phase. Like in the POT problem, they aim at finding a periodic timetable that minimizes perceived travel time (a weighted sum of in-train, transfer, and adaption time and transfer penalties) under the assumption that passenger demand is uniformly distributed over the period.…”

“…However, in contrast to the POT problem, they do not consider infrastructure constraints, arguing that these are not relevant in the strategic planning phase. In this paper, we use the approach developed in Polinder et al [2020] for strategic timetabling to compute an ideal timetable in the first phase of our solution approach. It is therefore described in more detail in Section 4.2.…”

“…In constraints (3.3) we model that each passenger will choose a route that minimizes his perceived travel time. We model this following the approach outlined in Polinder et al [2020] for strategic timetabling.…”

“…POT can be formulated as a mixed-integer linear program combining a periodic event scheduling model with an approach for modelling average perceived travel time including adaption time as developed in Polinder et al [2020] for strategic timetabling. However, the resulting model is very difficult to solve.…”

“…Therefore, in this paper we propose an iterative approach that combines (extended versions of) two existing approaches. First, we compute an ideal timetable, that is: a timetable that does not need to respect infrastructure restrictions, using the method proposed in Polinder et al [2020] for strategic timetabling. Secondly, we transform this ideal timetable into a feasible timetable, that is: make it satisfy the infrastructure restrictions, using an extension of the Lagrangian heuristic (LH) proposed in Cacchiani et al [2010] with the goal to find a timetable that stays as close as possible to the ideal timetable, but satisfies the infrastructure restrictions.…”