Public transport demand and supply management under uneven passenger distributions
Time: Mon 2022-06-13 14.00
Location: Kollegiesalen, Brinellvägen 8, Stockholm
Video link: https://kth-se.zoom.us/j/68428741605
Language: English
Subject area: Transport Science, Transport Systems
Doctoral student: Soumela Peftitsi , Transportplanering
Opponent: Professor Achille Fonzone,
Supervisor: Associate Professor Erik Jenelius, Transportplanering; PhD Oded Cats, Transportplanering
QC220511
Abstract
Overcrowding in public transport (also known as public transportation, public transit, or transit) systems due to increased travel mobility has become a major problem for public transport operators. Overcrowded transit stations and vehicles are connected to travel time variability and greater discomfort for the passengers. Uneven passenger distributions among lines, stations, trips or even among different compartments of the vehicle (e.g. individual cars of a multi-car rail vehicle) lead to inefficient capacity utilization and magnify the negative effects of crowding. To this end, there is a need to gain a deeper understanding of passenger travel behavior and the causes of the imbalanced passenger distribution as well as improve the capacity utilization and passenger travel experience through demand and supply management strategies.
Data-driven analysis has been conducted in Paper I to study the uneven distribution of passengers among individual cars of a transit vehicle and investigate the determinants of passengers' boarding choices. The thesis demonstrates the effect of crowding as well as the platform layout on passengers' boarding decisions for a case study to the metro network in Stockholm, Sweden. Paper I shows that in high-demand conditions passengers choose a train car making trade-offs between walking and in-vehicle crowding.
The increased understanding of passenger boarding behavior is used as the basis for proposing strategies that aim to improve capacity utilization and passenger travel experience. An existing transit assignment model is extended in Paper II to capture the effects of the uneven passenger distribution on passenger travel experience. This model is used as a tool for assessing demand and supply management strategies for case studies to the Stockholm metro network.
Improved vehicle capacity utilization can be reached through real-time crowding information provision systems as a means of controlling passenger demand. Passenger behavioral response to crowding information concerning individual train cars is modelled. The effect of information provision systems on passengers' travel choices and the experienced discomfort is evaluated in Paper III, considering different provision schemes and level of information. Passenger travel experience improves with the provisioning of crowing information, which is a result of the improved vehicle capacity utilization.
Finally, in Paper IV skip-stop policy is evaluated as a supply-management strategy under uneven passenger distributions among transit stations. This aims to accelerate the operation and improve passenger travel experience. A rule-based planning approach is adopted to determine the stopping pattern and investigate to what extent this rule can be a proxy for simulation-based frameworks. The results reveal that this policy can improve passenger travel experience but only under certain conditions in relation to passenger distribution at the stops along the line.