CoChat
Sign Up
Cited by 126Transportation Planning and OptimizationTransportation and Mobility InnovationsUrban Transport Systems Analysis

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

A dynamic stochastic model for evaluating congestion and crowding effects in transit systems

Open access
Cats, Oded, West, Jens, Eliasson, Jonas·2016·Transportation Research Part B: Methodological
DOI 10.1016/j.trb.2016.04.001
Open this paper in CoChat — free accountOpen PDF

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.trb.2016.04.001

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

  • Bus bunching results in unreliable services with negative implications for passengers and operators, including longer journey times, service delays, higher travel discomfort, risk of overcrowding and denied boarding, uneven headway and load distribution, and inefficient capacity utilization.

    “This phenomenon results in unreliable services, with a series of negative implications for passengers and operators—longer journey times, service delays, higher travel discomfort, risk of overcrowding and denied boarding, uneven headway and load distribution and an inefficient capacity utilization (Cats et al. 2016).”

    From Mitigating bus bunching with real-time crowding information (2023) · cites this paper as Cats et al. 2016

  • BusMezzo enforces strict capacity constraints.

    “The BusMezzo model enforces strict capacity constraints (Cats et al. 2016; Gavriilidou and Cats 2019).”

    From Mitigating bus bunching with real-time crowding information (2023) · cites this paper as Cats et al. 2016

  • BusMezzo assumes an explicit, disaggregate representation of PT system, which enables in-depth analysis of PT overcrowding and PT capacity reductions' effects on passengers' travel experience and network performance.

    “The BusMezzo model assumes an explicit, disaggregate representation of PT system, which enables in-depth analysis of the PT overcrowding (Cats et al. 2016) and PT capacity reductions’ (Cats and Jenelius 2018) effects on passengers’ travel experience and network performance.”

    From Mitigating bus bunching with real-time crowding information (2023) · cites this paper as Cats et al. 2016

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 38

  1. Babaei, 2014, The impact of irregular headways on seat availability, Transportmetrica A: Transport Science, 10, 483, 10.1080/23249935.2013.795198 · DOI
  2. Börjesson, 2014, Experiences from the Swedish value of time study, Transportation Research Part A, 59, 144
  3. Börjesson, 2012, Valuations of travel time variability in scheduling versus mean–variance models, Transportation Research Part B, 46, 855, 10.1016/j.trb.2012.02.004 · DOI
  4. Cats, 2014, Regularity-driven bus operations: principles, implementation and business models, Transport Policy, 36, 223, 10.1016/j.tranpol.2014.09.002 · DOI
  5. Cats, 2015, Modelling the impacts of public transport reliability and travel information on passengers’ waiting time uncertainty, EURO Journal of Transportation and Logistics,, 1
  6. Cats, 2011, Effect of real-time transit information on dynamic passenger path choice, Transportation Research Record, 2217, 46, 10.3141/2217-06 · DOI · Paper page
  7. Cats, 2012, Holding control strategies: a simulation-based evaluation and guidelines for implementation, Transportation Research Record, 2274, 100, 10.3141/2274-11 · DOI
  8. Cepeda, 2006, A frequency-based assignment model for congested transit networks with strict capacity constraints: characterization and computation of equilibria, Transportation Research Part B, 40, 437, 10.1016/j.trb.2005.05.006 · DOI
  9. Cominetti, 2011, Common-lines and passenger assignment in congested transit networks, Transportation Science, 35, 250, 10.1287/trsc.35.3.250.10154 · DOI
  10. de Cea, 1993, Transit assignment for congested public transport system: an equilibrium model, Transportation Science, 27, 133, 10.1287/trsc.27.2.133 · DOI
  11. de Palma, 2015, Discomfort in mass transit and its implication for scheduling and pricing, Transportation Research Part B, 71, 1, 10.1016/j.trb.2014.10.001 · DOI
  12. Fu, 2012, A review on transit assignment modelling approaches to congested networks: a new perspective, Procedia – Socical and Behavrioal Sciences, 54, 1145, 10.1016/j.sbspro.2012.09.829 · DOI
  13. Hamdouch, 2011, Schedule-based transit assignment model with vehicle capacity and seat availability, Transportation Research Part B, 45, 1805, 10.1016/j.trb.2011.07.010 · DOI
  14. Hamdouch, 2008, Scheduled-based transit assignment model with travel strategies and capacity constraints, Transportation Research Part B, 42, 663, 10.1016/j.trb.2007.11.005 · DOI
  15. Hamdouch, 2014, A new schedule-based transit assignment model with travel strategies and supply uncertainties, Transportation Research Part B, 67, 35, 10.1016/j.trb.2014.05.002 · DOI
  16. Jansson, 1992, A method for the route-choice problem in public transport systems, Transportation Science, 26, 246, 10.1287/trsc.26.3.246 · DOI
  17. Kim, 2014, Why do passengers choose a specific car of a metro train during the morning peak hours, Transportation Research Part A, 61, 249
  18. Kroes, E., Kouwenhoven, M., Debrincat, L., Pauget, N., 2013. On the value of crowding in public transport for Ile-De-France. OECD/ITF Discussion Paper 2013-18. Prepared for OECD/ITF Roundtable on Valuing Convenience in Public Transport. Available at: http://www.oecd-ilibrary.org/transport/on-the-value-of-crowding-in-public-tansport-for-ile-de-france_5k3z04fx2zq7-en (accessed 30.06.14).
  19. Kurauchi, 2003, Capacity constrained transit assignment with common lines, Journal of Mathematical Modelling and Algorithms, 2, 309, 10.1023/B:JMMA.0000020426.22501.c1 · DOI
  20. Lam, 1999, A stochastic user equilibrium assignment model for congested transit networks, Transportation Research Part B, 33, 351, 10.1016/S0191-2615(98)00040-X · DOI
  21. Leurent, 2014, A traffic assignment model for transit on a capacitated network: bi-layer framework, line sub-models and large-scale application, Transportation Research Part C, 47, 3, 10.1016/j.trc.2014.07.004 · DOI
  22. Li, 2011, Crowding and public transport: a review of willingness to pay evidence and its relevance in project appraisal, Transport Policy, 18, 880, 10.1016/j.tranpol.2011.06.003 · DOI
  23. Liu, 2010, Transit users’ route-choice modelling in transit assignment: a review, Transport Reviews, 30, 753, 10.1080/01441641003744261 · DOI
  24. Nuzzolo, 2012, Schedule-based assignment models with explicit capacity constraints for congested public transport networks, Transportation Research Part C, 20, 16, 10.1016/j.trc.2011.02.007 · DOI
  25. Nuzzolo, 2001, A doubly dynamic schedule-based assignment model for transit networks, Transportation Science, 35, 268, 10.1287/trsc.35.3.268.10149 · DOI
  26. Pel, 2014, Including passengers’ response to crowding in the Dutch national train passenger assignment model, Transportation Research Part A, 66, 111
  27. Poon, 2004, A dynamic schedule-based model for congested transit networks, Transportation Research Part B, 38, 343, 10.1016/S0191-2615(03)00026-2 · DOI
  28. Prud'homme, 2012, Public transport congestion costs: the case of Paris subway, Transport Policy, 21, 101, 10.1016/j.tranpol.2011.11.002 · DOI
  29. Schmöcker, 2011, Frequency-based transit assignment considering seat capacities, Transportation Research Part B, 45, 392, 10.1016/j.trb.2010.07.002 · DOI
  30. Schmöcker, 2008, A quasi-dynamic capacity constrained frequency-based transit assignment, Transportation Research Part B, 42, 925, 10.1016/j.trb.2008.02.001 · DOI
  31. Spiess, 1989, Optimal strategies: A new assignment model for transit networks, Transportation Research Part B, 23, 83, 10.1016/0191-2615(89)90034-9 · DOI
  32. Sumalee, 2009, Dynamic stochastic transit assignment with explicit seat allocation, Transportation Research Part B, 43, 895, 10.1016/j.trb.2009.02.009 · DOI
  33. Szeto, 2014, Transit assignment: Approach-based formulation, extragradient method, and paradox, Transportation Research Part B, 62, 51, 10.1016/j.trb.2014.01.010 · DOI
  34. Szeto, 2013, Reliability-based stochastic transit assignment with capacity constraints: Formulation and solution method, Transportation Research Part C, 35, 286, 10.1016/j.trc.2011.09.001 · DOI
  35. Toledo, 2010, Mesoscopic simulation for transit operations, Transportation Research Part C, 18, 896, 10.1016/j.trc.2010.02.008 · DOI
  36. Trozzi, 2013, Dynamic user equilibrium in public transport networks with passenger congestion and hyperpaths, Transportation Research Part B, 57, 266, 10.1016/j.trb.2013.06.011 · DOI
  37. Wardman, 2004, Public transport values of time, Transport Policy, 11, 363, 10.1016/j.tranpol.2004.05.001 · DOI
  38. Wardman, 2011, Twenty years of rail crowding valuation studies: evidence from lessons from British Experience, Transport Reviews, 31, 379, 10.1080/01441647.2010.519127 · DOI

Cited by

Sorted by citations

Metadata

Authors
Cats, O., West, J., & Eliasson, J.
Affiliations
KTH Royal Institute of Technology (SE)
Corresponding author
Cats, Oded
ORCID
Venue
Transportation Research Part B: Methodological
Publisher
Elsevier BV
Published
2016-07
Volume
89
Pages
43-57
ISSN
0191-2615 (ISSN-L)
DOI
10.1016/j.trb.2016.04.001
OpenAlex
W2339468066
Cited by
126
References
1
Citations by year
2026: 11 · 2025: 8 · 2024: 13 · 2023: 14 · 2022: 13 · 2021: 15 · 2020: 14 · 2019: 11 · 2018: 11 · 2017: 9 · 2016: 7
FWCI
19.18
Type
journal article
Language
en
Open access
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Transportation Research Part B Methodological (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Research Repository (Delft University of Technology) (submittedVersion)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Funders
Stockholm Public Transport Agency
Topics
  • Social Sciences › Transportation › Transportation Planning and Optimization
  • Social Sciences › Transportation › Transportation and Mobility Innovations
  • Physical Sciences › Engineering › Civil and Structural Engineering › Urban Transport Systems Analysis
Keywords
agent-based modeling, cost-benefit analysis, transit capacity, network reliability, metro extension

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