Social rerouting in public transport networks

The services of many public transportation systems are regulated by pre-defined timetables. In order to satisfy the demand at best, researchers and practitioners have been seeking robust demand-oriented scheduling approaches while keeping a low operation cost. Tactical decisions are limited to supply-side measures, typically made in the long term based on historical data. Such measures fail to quickly react to short-term changes in passenger demand and disturbances. Where the realized level of service (LOS) might be substantially different from what was expected, demand management measures, such as advising travelers to use specific routes in the interest of congestion and travel time of the entire population (social rerouting), can be implemented alongside supply-side measures to improve the LOS over different timescales.
In this study, we introduce multimodal social rerouting strategies to improve the LOS of public transport networks by asking a portion of the demand to change departure time, line or service. In fact, we balance network load by rerouting passengers using a centrally-coordinated information strategy. Such a strategy anticipates feedback effects in (over)crowding by incorporating behavioral responses to advice over different timescales. We explore theoretical and practical challenges by evaluating effectiveness and performance of strategies using real-world data from the Zürich public transport network.