Behaviorally Driven Train Timetable Design

The focus of this thesis is to include the passengers and their behavior inside the train timetable design. This is done through three main objectives: timetable design based on passenger satisfaction, exploitation of hybrid cyclicity and choice based revenue optimization. At first, a new Passenger Centric Train Timetabling Problem is introduced into the planning horizon of the passenger railway service. This problem is inter-disciplinary. It combines the discrete choice theory, that models the passengers’ behavior, and operations research, that decides on the departure times of the trains (i.e. the timetable). The attributes affecting the passengers’ choices with respect to the operated timetable are quantified into a single variable of passenger satisfaction. The objective of the proposed model is the trade-off between the profit of the train operating company and the overall satisfaction of the passengers. The problem is tested on the case study of the morning peak hours in S-train network of Canton Vaud in Switzerland. The results not only confirm that the passenger centric timetables outperform the operational timetable of Swiss Federal Railways (SBB), but they also demonstrate that there is a considerable gap between the performance of the cyclic and the non-cyclic timetable. The cause of this gap are the cyclicity constraints and therefore, new types of hybrid cyclicity are proposed and tested. The aim of the hybrid cyclic timetables is to provide similar level of flexibility (passenger satisfaction) as the non-cyclic timetables while keeping a certain level of regularity (cyclicity). The regularity is taken care of by the design and the flexibility is evaluated upon solving of the previously defined Passenger Centric Train Timetabling Problem. The new types of timetables are tested against the existing types on the case study of one day in the whole network of Israeli Railways. It is shown that the hybrid cyclic timetable can achieve both benefits (regularity and flexibility) at the same time. In the last part of this thesis, the passengers’ actual choices are obtained through a discrete choice model. The model takes into account fundamental principles in economics such as demand elasticity, ticket price and opt-out option for passengers. Therefore, the probabilistic Elastic Passenger Centric Train Timetabling Problem provides more realistic solutions. Moreover, since the choice is explicitly modeled, the new problem is integrated with a ticket pricing, in order to improve the level of service. In other words, to prevent overcrowding or to secure the service for passengers who need it the most, etc. To summarize, this thesis makes significant contributions in the conceptual design of