Public transport serves the society by providing cheap and fast mobility services. Due to long term experiences over decades,
the provided services are highly reliable and affordable. Traditionally, routes, intervals and vehicles are planned top
down based on a priori knowledge about the traveller flows and desired interchanges. Due to the slow changing nature
of traveller flows and a huge basis of domain knowledge, this planning process works reasonably well when every actor
involved is on time. However, in case of short term interruptions, delays or even cancellations ad hoc dispatching is necessary
to counteract the disruption. In those situations, two factors limit the service quality. First, the dispatcher only has a
priori knowledge about the local situation. Thus, it is impossible to make optimal dispatching decisions for all travellers.
Second, the dispatcher’s reactions to interruptions are not disseminated efficiently to the affected travellers. This often creates
uncertainty (Cambridge Systematics, 1999), which limits the travel experience and the perceived service quality (EN
13816, 2002).
In former times, it was impossible to gather and process individual journey information for each traveller in a timely
manner. However, this has changed due to the wide availability of modern communication systems like smartphones,
mobile data plans and high performance servers. Having today’s communication and data processing capabilities, it is possible
to collect, process, and include in situ information from all travellers within the operational decision processes and to
disseminate timetable changes in real time. Informing the traveller about dispatching decisions or timetable changes