Interchange stations are essential for a high-quality public transport system. Many passengers pass through a station during the course of a day and the time spent at a station has a large effect on their experience of the whole journey. In this study, we aim to improve the passenger experience at a bus terminal by minimizing the walking distances for all passengers. To this end, an integer linear optimization model which allocates bus lines to the stops of a bus terminal is presented. The model is tested in a numerical experiment using synthetic passenger data. Two alternative approaches, either randomly allocated or based on the number of non-transferring passengers, are used for comparisons. The average improvement in relation to the random allocation strategy is 13%, which shows that the allocation approach has potential. It is thus of interest to collect data from a real bus terminal to further explore the model and the potential benefits it can provide.

Interchange stations with their connections between modes and lines are central for a high quality public transport system. Bus access at the station needs to operate reliably and efficiently in order to prevent congestion and queues. Here, a discrete event simulation model of vehicle movements and interactions at bus terminals is developed and implemented. The model has a modular approach, where common spatial sections at terminals are represented by modules that can be combined into various terminal layouts. These modules describe the events a vehicle may go through in a particular section of the terminal, such as arriving to a bus stop or stopping at a traffic light at the exit. The model can be used in planning processes, both for new terminals and redesign of existing ones, and is able to describe the detailed movements and interactions between vehicles that occur at larger terminals. The model is tested in a numerical experiment representing Norrköping interchange station in Sweden. The experiment shows that the model is able to evaluate and compare different scenarios and can thus be a useful tool in planning processes.