This paper studies the influence of weather on the public transport (PT) ridership of the Swiss city of Zurich. The Zurich PT network is widely recognized as one of the best in the world; to continue guaranteeing its efficiency and attractiveness it is essential to cope with the weather conditions, which can induce a change in the travel demand that can negatively affect, if not taken into account, the performance of the transport network.This paper first introduces the considered sources of data and their behavior over time and space. It then investigates, by means of analytical and data science techniques, the spatio-temporal correlations of the selected weather parameters on the vehicle occupancy, which is chosen as ridership measure representative of the PT usage.Results show that rain affects significantly the PT ridership, and that the extent deeply depends on the time, the day type and the section location in the network. The spatial and temporal differences in the way weather affects the occupancy of the PT vehicles are among the major findings of this work, and could be used by the PT provider to adjust the service and optimally allocate the resources (i.e., tram types and compositions) depending on where and when they are more necessary.
Weather Effects on the Public Transport Ridership of the City of Zurich at a Stop-to-stop Level
Gallo, F;
2023-01-01
Abstract
This paper studies the influence of weather on the public transport (PT) ridership of the Swiss city of Zurich. The Zurich PT network is widely recognized as one of the best in the world; to continue guaranteeing its efficiency and attractiveness it is essential to cope with the weather conditions, which can induce a change in the travel demand that can negatively affect, if not taken into account, the performance of the transport network.This paper first introduces the considered sources of data and their behavior over time and space. It then investigates, by means of analytical and data science techniques, the spatio-temporal correlations of the selected weather parameters on the vehicle occupancy, which is chosen as ridership measure representative of the PT usage.Results show that rain affects significantly the PT ridership, and that the extent deeply depends on the time, the day type and the section location in the network. The spatial and temporal differences in the way weather affects the occupancy of the PT vehicles are among the major findings of this work, and could be used by the PT provider to adjust the service and optimally allocate the resources (i.e., tram types and compositions) depending on where and when they are more necessary.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.