Public Transport and Passengers: Optimization Models that Consider Travel Demand

Public transport is an indispensable part of our society. It increases mobility for all, enables efficient transportation in densely populated areas, and protects the environment with lowest emissions per passenger kilometer. To reap its benefits, an effective public transport system must be created attracting large numbers of passengers. In the first part of this thesis, we present integrated models to optimize public transport services while estimating the corresponding passenger choices. The first study compares different timetable evaluation functions for consistency and gives further motivation for the integration of passenger choice models into optimization models. In the next two studies, we present novel optimization models with integrated demand estimation for the steps of timetabling and line planning, respectively. The resulting public transport services are designed for the passenger demand they generate. The second part of this thesis deals with new and more flexible forms of public transport: mobility on demand. In order to assess the consequences of large-scale on-demand services on cities and regions, travel demand models need to be extended to determine the service level of on-demand services. Both studies in this part present solution algorithms for a vehicle scheduling problem of on-demand services to estimate the required vehicle fleet size and distance traveled

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