Disruptions, events, incidents, and closures are daily characteristics of urban transport systems. Yet, our understanding of how people change their travel behaviours in each situation is limited. Improving our understanding of behaviour under different scenarios, and development of a robust model of behaviour, would be beneficial to transport authorities seeking to promote behaviour change to improve services.
This project will undertake analyses of changes in travel behaviour following disruption (events, incidents, road closures) and develop new ABMs that predict the outcomes of future disruptions. The project is in collaboration with Transport for West Midlands in order to provide real-world application and context for the modelling.
Supervisors: Ed Manley, Manon Prédhumeau
Project partner: Transport for West Midlands
Application deadline: 21st July 2023
For more details, visit https://datacdt.org/projects/predicting-travel-patterns-under-disruption-and-change/