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Cited by 187Infrastructure Resilience and Vulnerability AnalysisTransportation Planning and OptimizationTransportation and Mobility Innovations

The DOI matches its Crossref record.

Dynamic Vulnerability Analysis of Public Transport Networks: Mitigation Effects of Real-Time Information

Cats, Oded, Jenelius, Erik·2014·Networks and Spatial Economics
DOI 10.1007/s11067-014-9237-7
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Crossref · 10.1007/s11067-014-9237-7

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  • BusMezzo has been applied for analysing the impacts of real-time information concerning subsequent vehicle arrivals on travel times and RTCI on instantaneous route choices.

    “It has been also applied for analysing the impacts of real-time information (RTI) concerning subsequent vehicle arrivals on travel times (Cats et al. 2011a; Cats and Jenelius 2014) and real-time crowding information (RTCI) on instantaneous route choices (Drabicki et al. 2021b).”

    From Mitigating bus bunching with real-time crowding information (2023) · cites this paper as Cats and Jenelius 2014

Citations

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Research works printed but not linked: 27

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  2. Ball MO, Golden BL, Vohra RV (1989) Finding the most vital arcs in a network. Oper Res Lett 8:73–76 · DOI
  3. Berche B, von Ferber C, Holovatch T, Holovatch Y (2009) Resilience of public transport networks against attacks. Eur Phys J B 71:125–137 · DOI
  4. Berdica K (2002) An introduction to road vulnerability: what has been done, is done and should be done. Transp Policy 9:117–127 · DOI
  5. Carson Y, Maria A (1997) Simulation optimization: methods and applications. Proceedings of the 1997 Winter Simulation Conference, 118–126 · DOI
  6. Cats O (2013) Multi-agent transit operations and assignment model. Procedia Comput Sci 19:809–814, The 2nd International Workshop on Agent-based Mobility, Traffic and Transportation Models, Methodologies and Applications (ABMTRANS) · DOI
  7. Cats O, Koutsopoulos HN, Burghout W, Toledo T (2011a) Effect of real-time transit information on dynamic passenger path choice. Transp Res Rec 2217:46–54 · DOI · Paper page
  8. Cats O, Larijani AN, Burghout W, Koutsopoulos HN (2011b) Impacts of holding control strategies on transit performance: a bus simulation model analysis. Transp Res Rec 2216:51–58 · DOI · Paper page
  9. Colak S, Lus H, Atligan AR (2010) Vulnerability of networks against critical links failure. Available at: http://arxiv.org/abs/1012.5961v2 · arXiv
  10. Criado R, Hernández-Bermejo B, Romance M (2007) Efficiency, vulnerability and cost: an overview with applications to subway networks worldwide. Int J Bifurcation Chaos 17:2289–2301 · DOI
  11. Crucitti P, Latora V, Porta S (2007) Centrality measures in spatial networks of urban streets. Phys Rev E 73:1–5
  12. Derrible S, Kennedy C (2010) The complexity and robustness of metro networks. Physica A 389:3678–3691 · DOI
  13. Dowling R, Skabardonis A, Alexiadis V (2004) Traffic analysis toolbox volume III: guidelines for applying traffic microsimulation modeling software. U.S. Department of Transportation, Federal Highway Administration (FHA), Washington DC
  14. Freeman LC, Borgatti SP, White DR (1991) Centrality in valued graphs: a measure of betweenness based on network flow. Soc Networks 13:141–154 · DOI
  15. Jenelius E, Mattsson L-G (2012) Road network vulnerability analysis of area-covering disruptions: a grid-based approach with case study. Transp Res A 46:746–760
  16. Jenelius E, Petersen T, Mattsson L-G (2006) Importance and exposure in road network vulnerability analysis. Transp Res A 40:537–560
  17. Latora V, Marchiori M (2007) A measure of centrality based on network efficiency. New J Phys 9:188 · DOI
  18. Mahmassani HS, Jayakrishnan R (1991) System performance and user response under real-time information in a congested traffic corridor. Transp Res A 25:293–307 · DOI
  19. Murray-Tuite PM, Mahmassani HS (2004) Methodology for the determination of vulnerable links in a transportation network. Transp Res Rec 1882:88–96 · DOI
  20. Nicholson AJ, Du ZP (1994) Improving network reliability: a framework. In: Proceedings of 17th Australian Road Research Board Conference, 3:1–17
  21. Ratliff HD, Sicilia GT, Lubore SH (1975) Finding the n most vital links in flow networks. Manag Sci 21:531–539 · DOI
  22. Scott DM, Novak DC, Aultman-Hall L, Guo F (2006) Network robustness index: a new method for identifying critical links and evaluating the performance of transportation networks. J Transp Geogr 14:215–227 · DOI
  23. Sohn J (2006) Evaluating the significance of highway network links under the flood damage: an accessibility approach. Transp Res A 40:491–506
  24. Taylor MAP, Susilawati (2012) Remoteness and accessibility in the vulnerability analysis of regional road networks. Transp Res A 46:761–771
  25. Toledo T, Cats O, Burghout W, Koutsopoulos HN (2010) Mesoscopic simulation for transit operations. Transp Res C 18:896–908 · DOI
  26. von Ferber C, Holovatch T, Holovatch Y, Palchykov V (2009) Public transport networks: empirical analysis and modeling. Eur Phys J B 68:261–275 · DOI
  27. von Ferber C, Berche B, Holovatch T, Holovatch Y (2012) A tale of two cities: vulnerabilities of the London and Paris transit networks. J Transp Secur 5(3):199–216 · DOI

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Metadata

Authors
Cats, O., & Jenelius, E.
Affiliations
KTH Royal Institute of Technology (SE)
Corresponding author
Cats, Oded
ORCID
Venue
Networks and Spatial Economics
Publisher
Springer Science and Business Media LLC
Published
2014-04-18
Volume
14
Issue
3-4
Pages
435-463
ISSN
  • 1566-113X (ISSN-L)
  • 1572-9427
DOI
10.1007/s11067-014-9237-7
OpenAlex
W2058586158
Cited by
187
References
0
Citations by year
2026: 17 · 2025: 19 · 2024: 19 · 2023: 9 · 2022: 20 · 2021: 19 · 2020: 18 · 2019: 15 · 2018: 10 · 2017: 12 · 2016: 12 · 2015: 12 · 2014: 5
FWCI
24.70
Type
journal article
Language
en
Open access
closed
Licence
www.springer.com/tdm (tdm)
Locations
  • Networks and Spatial Economics (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Resilience and Vulnerability Analysis
  • Social Sciences › Transportation › Transportation Planning and Optimization
  • Social Sciences › Transportation › Transportation and Mobility Innovations
Keywords
real-time information, service disruption, betweenness centrality, link importance, passenger flow, vehicle flow, Stockholm, spillover effects, disruption mitigation

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