During COVID-19, certain means were proposed to improve crowd management in the Birmingham New Street railway station. To validate the current system of crowd management in the station, this paper examines the rail passenger flow in the concourse of the Birmingham New Street railway station and the passenger interactions and queueing phenomena associated with it, mainly at the ticket machines, offices and gates, prior to and during the implementation of COVID-19 measures. The passenger behaviour in the concourse of the station was simulated using the SIMUL8 event-based simulation modelling package. Three different scenarios were modelled to analyse the changes and impacts from pre-COVID-19 and within the COVID-19 context. The results revealed that passenger behaviour in railway stations is changing due to COVID-19. Specifically, passengers are more likely to buy tickets using their smartphones or online prior to or whilst entering the station so that they can go through the station concourse with minimal queuing times and avoid contact with a facility of common use at the station, whereas those without tickets are more likely to be in a queue to buy their tickets in the station. For pre-COVID, the results showed that even with a reduced number of ticket machines, overcrowding inside the station was unlikely to occur, as 80% of all passengers in the simulation completed service within a 15-minute time frame. However, during implementation of COVID-19 measures, as the number of passengers using the station dropped significantly and more passengers bought their tickets using their smartphones and/or online, queueing times were also shorter, and thus passengers spent less time in the system. The simulation results were in accordance with the expected practice; hence the effectiveness of the simulation model was verified. Overall, as a result of this study, the following suggestions to improve crowd management in a railway passenger station concourse are proposed: encourage passengers to purchase tickets on their smartphones, remove ticket gates and replace them with sensors, and provide a one-way passenger flow system in the main concourse of the station.
Due to climate change, more sustainable passenger and freight transport is in need. Rail is considered a more sustainable mode of transport compared to others such as road transport. Usage of rail lines that are currently under-utilised could help increase the sustainability of transport through enhanced utilisation of them. This study looks at the Marston Vale Line, identifying it as under-utilised, and through the use of event-based simulation modelling, observes the current utilisation level and develops ways in which the spare capacity can be utilised, with more passenger services, as well as local rail freight, which is identified as a potential use of spare capacity on the Marston Vale Line. Possible local freight that can be transported by rail is investigated and combined with current and possible additional passenger services in varying levels, in five different scenarios, which are evaluated to propose the best workable option for the Marston Vale Line, with journey time and reliability also considered. Particular theoretical attention is proposed to create a more environmentally friendly mode for the transportation of passengers and freight, and not just shifting more from road to rail using the idea that rail transport is more sustainable than road transport.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.