Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 47Transportation Planning and OptimizationRailway Systems and Energy EfficiencyEvacuation and Crowd Dynamics

The DOI matches its Crossref record.

Train Overcrowding: Investigation of the Provision of Better Information to Mitigate the Issues

Preston, John, Pritchard, James, Waterson, Ben·2017·Transportation Research Record: Journal of the Transportation Research Board

Abstract

Crowded trains are a feature of many railway networks and adversely affect both train passengers and rail operators. For passengers, the lack of space or inability to get a seat can lead to a lack of physical comfort, reduced productivity, and increased stress. Crowded trains can also lead to problems boarding and alighting that increase dwell times and make it harder for operators to provide a reliable service. Reducing levels of crowding is therefore desirable, but achieving this goal by increasing capacity is not always practical, and other measures must be considered. Some passengers have shown willingness to change their behavior to avoid crowding—for example, by waiting for a later train—and measures to encourage such behavioral changes more widely could be beneficial overall. Better information provision could be one such measure, and so a stated preference survey was undertaken on a commuter and airport service to investigate this issue further. It was found that the provision of information about crowding levels and seating availability on alternative trains would encourage some passengers to wait for a less-crowded train. Although the willingness of passengers to wait for a later train varied by both the purpose of the trip and the station of origin, the findings suggest that real-time information would improve the passenger experience and could form the basis of a revenue-neutral demand-management system. The implications for station design are particularly pertinent for countries such as the United States, where significant investment in new passenger rail systems is expected.

Overview

Integrity signals

Registry

Crossref · 10.3141/2649-01

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 11

  1. HennL., KarpouzisG., and SloanK. A Review of Policy and Economic Instruments for Peak Demand Management in Commuter Rail. In Proceedings of the Australasian Transport Research Forum, Canberra, Australia, September 29—October 1, Planning and Transport Research Centre, Curtin University of Technology, Bentley, WA. http://www.scopus.com/inward/record.url?eid=2-s2.0-84866239741&partnerID=40&md5=3fa24ac3b06b58526c861c5c41ffa27b.
  2. Davidson B., Presented at 34th Australasian Transport Research Forum
  3. Nair N., 2015, Passenger Rail Usage: 2014–15 Quarter 4 Statistical Release
  4. CoxT., HoudmontJ., and GriffithsA. Rail Passenger Crowding, Stress, Health and Safety in Britain. Transportation Research Part A: Policy and Practice, Vol. 40, No. 3, 2006, pp. 244–258. http://linkinghub.elsevier.com/retrieve/pii/S096585640500100X. Accessed Feb. 28, 2014. · DOI
  5. PelA. J., BelN. H., and PietersM. Including Passengers’ Response to Crowding in the Dutch National Train Passenger Assignment Model. Transportation Research Part A: Policy and Practice, Vol. 66, No. 1, 2014, pp. 111–126. http://dx.doi.org/http://dx.doi.org/10.1016/j.tra.2014.05.007. · DOI
  6. Sakairi S., Presented at 11th World Congress on Railway Research
  7. WardmanM., and WhelanG. Twenty Years of Rail Crowding Valuation Studies: Evidence and Lessons from British Experience. Transport Reviews, Vol. 31, No. 3, 2011, pp. 379–398. http://dx.doi.org/10.1080/01441647.2010.519127. · DOI
  8. Passenger Demand Forecasting Council, 2009, Passenger Demand Forecasting Handbook, Part C, Version 3
  9. Kim J.-K., 2010, Transportation Research Record: Journal of the Transportation Research Board, 119
  10. ArentzeT. A., and MolinE. J. E. Travelers’ Preferences in Multimodal Networks: Design and Results of a Comprehensive Series of Choice Experiments. Transportation Research Part A: Policy and Practice, Vol. 58, 2013, pp. 15–28. http://dx.doi.org/http://dx.doi.org/10.1016/j.tra.2013.10.005. · DOI
  11. Vovsha P., 2014, Presented at 93rd Annual Meeting of the Transportation Research Board, 1

Cited by

Metadata

Authors
Preston, J., Pritchard, J., & Waterson, B.
Affiliations
University of Southampton (GB)
Corresponding author
Pritchard, James
Venue
Transportation Research Record: Journal of the Transportation Research Board
Published
2017-01
Volume
2649
Issue
1
Pages
1-8
ISSN
  • 0361-1981 (ISSN-L)
  • 2169-4052
OpenAlex
W2565971900
Cited by
47
References
0
Citations by year
2026: 4 · 2025: 3 · 2024: 11 · 2023: 4 · 2022: 8 · 2021: 5 · 2020: 6 · 2019: 2 · 2018: 2 · 2017: 2
FWCI
4.56
Type
journal article
Language
en
Open access
closed
Locations
  • Transportation Research Record Journal of the Transportation Research Board (publishedVersion)
  • ePrints Soton (University of Southampton) (acceptedVersion)
Topics
  • Social Sciences › Transportation › Transportation Planning and Optimization
  • Social Sciences › Transportation › Railway Systems and Energy Efficiency
  • Social Sciences › Safety Research › Evacuation and Crowd Dynamics
Keywords
passenger crowding, seat availability, passenger behavior, willingness to wait, stated preference, commuter rail, airport rail link, demand management, station design, dwell time, passenger experience

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review