Simulating the effects of real-time crowding information in public transport networks

The objective of this paper is to understand the consequences of providing real-time information on crowding levels (RTI-CL) in public transport networks. We propose to extend the mesoscopic, simulation-based assignment model with the passengers' knowledge of instantaneous crowding levels onboard the public transport vehicles. We illustrate the results on a sample transit network, where we investigate the arising changes in network performance and journey experience as a result of RTI-CL provision. We demonstrate that effects of providing the crowding information in real-time on en-route path choices is strongly related to number of assumptions that we address in the paper. The resulting changes are dependent on: network congestion level (the effects are mostly pronounced in moderately congested networks), passengers' behaviour (increased sensitivity to crowding induces higher variability in vehicle loads), the RTI-CL penetration rate (network performance becomes worse with ubiquitous access to information) and information provision type (smoothed information over recent vehicle runs leads to higher accuracy than instantaneous information based on the single latest run only). Based on these, we formulate conclusions for further studies, larger-scale applications and practical implementation of real-time passenger crowding information systems.