Robustness Of Urban Public Transport Networks
Free (open access)
S. Tahmasseby & R. van Nes
Analyses of public transport networks are usually based on a deterministic point of view: it is assumed that all components of the system perform as planned. In reality, however, there are many disturbances influencing public transport services such as variation in demand, service provision, and infrastructure availability. The question is how these disturbances affect the quality of the transport services. As a first step in answering this question a model has been developed that describes the consequences for operators and travellers of variation in infrastructure availability due to disturbances such as incidents, weather, and road works. The model describes the way events might affect infrastructure availability, the resulting impact on the public transport service network (detours, cancelled services) and assesses the outcome for travellers and operators in terms of costs. The model is applied to theoretical networks to illustrate the importance of considering such disturbances in the analysis of public transport networks. Furthermore, the analysis provides insight into possibilities to improve the robustness of public transport service networks by adjusting the service network design or by introducing additional shortcut possibilities in the infrastructure network for detours in case of disturbances. Keywords: robustness, public transport networks, infrastructure availability. 1 Introduction For the evaluation of public transport networks assignment models are applied using OD-matrices and descriptions of public transport networks. These evaluation models are based on a deterministic perspective: all types of input are assumed to be known exactly and to be constant over time. These are clearly unrealistic assumptions. The demand pattern varies between hours and over days, while transport supply varies as well, either due to all kinds of organisational aspects in a public transport company, or due to changes in the
robustness, public transport networks, infrastructure availability.