Nothing Special   »   [go: up one dir, main page]

Skip to main content

Advertisement

Log in

Have they bunched yet? An exploratory study of the impacts of bus bunching on dwell and running times

  • Original Paper
  • Published:
Public Transport Aims and scope Submit manuscript

Abstract

If transit agencies wish to retain and attract riders, they need to provide reliable and efficient services. Transit agencies tend to run high-frequency bus routes during peak hours, and in many cities, different routes can also overlap along major corridors. In some instances, consecutive buses can arrive at a shared stop simultaneously or one bus may arrive while another bus is currently servicing the stop. This phenomenon, known as bus bunching, can delay buses and passengers, and is usually inefficient. In this study, we attempt to understand how bus bunching from the same or different routes can impact bus operations, specifically dwell and running times. This research uses stop-level records obtained from automatic vehicle location (AVL) and automatic passenger counter (APC) systems from TriMet, Portland, OR. Using linear modeling, we find that bus bunching increases both dwell and running times. Specifically, when different routes bunch or are scheduled to arrive at a bus stop within a short time frame, or when buses from the same route arrive with a short time frame, dwell times increase by ~10 s. Similarly, bus bunching from the same route or different route prolongs running times by ~40 s. Our findings suggest that bus schedulers and operators should consider adding more time between consecutive buses from different routes at shared stops to minimize the negative impacts that we observed from bus bunching.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Abkowitz M, Engelstein I (1983) Factors affecting running time on transit routes. Transp Res Part A 17(2):107–113

    Article  Google Scholar 

  • Barr J, Beaton E, Chiarmonte J, Orosz T (2010) Select bus service on Bx12 in New York City. Transp Res Rec 2145:40–48

    Article  Google Scholar 

  • Berrebi SJ, Watkins KE, Laval JA (2015) A real-time bus dispatching policy to minimize passenger wait on a high frequency route. Transp Res Part B Methodol 81(2):377–389

    Article  Google Scholar 

  • Boyle D (2006) Fixed-route transit ridership forecasting and service planning methods. TCRP Synthesis 66. In: TCRP (ed) TCRP synthesis. Washington, D.C

  • Cats O, Larijani A, Ólafsdóttir Á, Burghout W, Andréasson I, Koutsopoulos H (2012) Bus-holding control strategies. Transp Res Rec 2274:100–108

    Article  Google Scholar 

  • Daganzo CF (2009) A headway-based approach to eliminate bus bunching: Systematic analysis and comparisons. Transp Res Part B Methodol 43(10):913–921

    Article  Google Scholar 

  • Daganzo CF, Pilachowski J (2011) Reducing bunching with bus-to-bus cooperation. Transp Res Part B Methodol 45(1):267–277

    Article  Google Scholar 

  • Daskalakis N, Strathopoulos A (2008) Users’ perceptive evaluation of bus arrival time deviations in stochastic networks. J Public Transp 11(4):25–38

    Article  Google Scholar 

  • Diab E, El-Geneidy A (2012) Understanding the impacts of a combination of service improvement strategies on bus running time and passenger’s perception. Transp Res Part A Policy Pract 46(3):614–625

    Article  Google Scholar 

  • Diab E, El-Geneidy A (2013) Variation in bus transit service: understanding the impacts of various improvement strategies on transit service reliability. Public Transp Plan Oper 4(3):209–231

    Article  Google Scholar 

  • Diab E, El-Geneidy A (2014) Transitory optimism: Changes in passenger perception following bus service improvement over time. Transp Res Rec 2415:97–106

    Article  Google Scholar 

  • Diab E, El-Geneidy A (2015) The far side story: measuring the benefits of bus stop location on transit performance. Transp Res Rec 2538:1–10

    Article  Google Scholar 

  • Diab E, Badami M, El-Geneidy A (2015) Bus transit service reliability and improvement strategies: integrating the perspectives of passengers and transit agencies in North America. Transp Rev 35(3):292–328

    Article  Google Scholar 

  • Dueker KJ, Kimpel TJ, Strathman JG, Callas S (2004) Determinants of bus dwell time. J Public Transp 7(1):21–40

    Article  Google Scholar 

  • Eberlein X, Wilson N, Bernstein D (2001) The holding problem with real-time information available. Transp Sci 35(1):1–18

    Article  Google Scholar 

  • El-Geneidy A, Vijayakumar N (2011) The effects of articulated buses on dwell and running times. J Public Transp 14(3):63–86

    Article  Google Scholar 

  • El-Geneidy A, Strathman JG, Kimpel TJ, Crout D (2006) The effects of bus stop consolidation on passenger activity and transit operations. Transp Res Rec 1971:32–41

    Article  Google Scholar 

  • Feng W, Figliozzi M (2015) Empirical analysis of bus bunching characteristics based on bus AVL/APC data. In: Paper presented at the 94th Annual Meeting of the Transportation Research Board, Washington, D.C

  • Figliozzi M, Feng W, Lafferriere G (2012) A study of headway maintenance for bus routes: causes and effects of “bus bunching” in extensive and congested service areas Civil and Environmental Engineering Faculty Publications and Presentations (vol. Paper 96). Portland, Oregon

  • Hammerle M, Haynes M, McNeil S (2005) Use of automatic vehicle location and passenger count data to evaluate bus operations. Transp Res Rec 1903:27–34

    Article  Google Scholar 

  • Hensher D, Stopher P, Bullock P (2003) Service quality—developing a service quality index in the provision of commercial bus contracts. Transp Res Part A Policy Pract 37(6):499–517

    Article  Google Scholar 

  • Hickman M (2001) An analytic stochastic model for the transit vehicle holding problem. Transp Sci 35(3):215–237

    Article  Google Scholar 

  • Hollander Y (2006) Direct versus indirect models for the effects of unreliability. Transp Res Part A Policy Pract 40(9):699–711

    Article  Google Scholar 

  • Holroyd E, Scraggs D (1996) Waiting times for buses in Central London. Traffic Eng Control 8(3):158–160

    Google Scholar 

  • Kimpel T, Strathman J, Bertini R, Callas S (2005) Analysis of transit signal priority using archived TriMet bus dispatch system data. Transp Res Rec 1925:156–166

    Article  Google Scholar 

  • Levine J, Torng G (1997) Dwell time effects of low-floor bus design. J Transp Eng 120(6):829–914

    Google Scholar 

  • Levinson H (1983) Analyzing transit travel time performance. Transp Res Rec 915:1–6

    Google Scholar 

  • Merevick T (2015) New CTA system might finally reduce awful bus-bunching issues Thrillist. Retrieved 14 March, 2016, from http://www.thrillist.com/news/chicago/new-cta-system-might-finally-reduce-awful-bus-bunching-issues

  • Moreira-Matias L, Ferreira C, Gama J, Mendes-Moreira J, de Sousa JF (2012) Bus Bunching detection by mining sequences of headway deviations. In: Perner P (ed) Advances in data mining. applications and theoretical aspects, vol 7377. Springer, Berlin Heidelberg, pp 77–91

  • Moreira-Matias L, Gama J, Mendes-Moreira J, de Sousa JF (2014) An incremental probabilistic model to predict bus bunching in real-time. Lect Notes Comput Sci 8819:227–238

    Article  Google Scholar 

  • Moreira-Matias L, Mendes-Moreira J, de Sousa JF, Gama J (2015) Improving mass transit operations by using AVL-based systems: a survey. IEEE Trans Intell Transp Syst 16(4):1636–1653

    Article  Google Scholar 

  • Paulley N, Balcombe R, Mackett R, Titheridge H, Preston JM, Wardman MR, White P (2006) The demand for public transport: the effects of fares, quality of service, income and car ownership. Transp Policy 13(4):295–306

    Article  Google Scholar 

  • Provost A-M (2015) Fiabilité des autobus de la STM: Nombre de plaintes en hausse. TVA Retrieved 13 March, 2016, from http://tvanouvelles.ca/lcn/infos/regional/montreal/archives/2015/05/20150521-052752.html

  • Simcoe L (2015) TTC turns to tech to tame bus ‘bunching’. Metro. Retrieved 14 March, 2016, from http://metronews.ca/news/toronto/1374711/ttc-turns-to-tech-to-tame-bus-bunching/

  • Stewart C, El-Geneidy A (2014) All aboard at all doors: route selection and running-time savings estimation for multiscenario all-door bus boarding. Transp Res Rec 2418:39–48

    Article  Google Scholar 

  • Strathman J, Dueker K, Kimpel T, Gerhart R, Turner K, Taylor P, Hopper H (1999) Automated bus dispatching, operations control, and service reliability baseline analysis. Transp Res Rec 1666:28–36

    Article  Google Scholar 

  • Strathman J, Dueker K, Kimpel T, Gerhart R, Turner K, Taylor P, Griffin D (2000) Service reliability impacts of computer-aided dispatching and automatic location technology: a Tri-Met case study. Transp Q 54(3):85–102

    Google Scholar 

  • Suprenant-Legault J, El-Geneidy A (2011) Introduction of a reserved bus lane: Impact on bus running time and on-time performance. Transp Res Rec 2218:10–18

    Article  Google Scholar 

  • TCRP (2013a) Quality of service concepts transit capacity and quality of service manual, 3rd edn. TRB, Washington, D.C.

    Google Scholar 

  • TCRP (2013b) Quality of service methods transit capacity and quality of service manual, 3rd edn. TRB, Washington, D.C.

    Google Scholar 

  • Vuchic V (2005) Urban transit: operations, planning and economics. Wiley, Indianapolis

    Google Scholar 

  • Yoh A, Iseki H, Smart M, Taylor BD (2011) Hate to wait: Effects of wait time on public transit travelers’ perceptions. Transp Res Rec 2216:116–124

    Article  Google Scholar 

Download references

Acknowledgments

We thank TriMet for providing the data for this study, and particularly Steve Callas and Miles Crumley. We thank Charis Loong for collecting bus stop environment data. This work was funded by a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant. We also would like to thank the three anonymous reviewers for their feedback on the earlier version of the manuscript. The ideas and findings presented in this paper represent the authors’ views in an academic exercise.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ahmed El-Geneidy.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Verbich, D., Diab, E. & El-Geneidy, A. Have they bunched yet? An exploratory study of the impacts of bus bunching on dwell and running times. Public Transp 8, 225–242 (2016). https://doi.org/10.1007/s12469-016-0126-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12469-016-0126-y

Keywords

Navigation