Technical Papers
Oct 4, 2017

Individual and Synergetic Effects of Transit Service Improvement Strategies: Simulation and Validation

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 143, Issue 12

Abstract

Assessment of transit service improvements such as bus lanes, allowing boarding through all doors, and headway-based holding control requires detailed simulation capabilities. However, because the usage of models advanced enough to simultaneously analyze physical and operational measures has been limited, their validity has hitherto remained low. This paper assesses the implementation of several bus service improvement measures in a simulation model. The paper analyzes the effect of isolated and combinations of measures, and validates the model using field experiment data. The model predicted travel time improvements accurately (1–2% difference), while overestimating some of the headway variability effects. The three tested measures exercised negative synergy effects, with their combined effect being smaller than the sum of their marginal contributions, except for headway-based holding, which exercised positive synergy effects with the two other measures.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

Part of this work was sponsored by the Stockholm County Council.

References

Abdelghany, K. F., Abdelghany, A. F., Mahmassani, H. S., and Abdelfatah, A. S. (2006). “Modeling bus priority using intermodal dynamic network assignment-simulation methodology.” J. Pub. Transp., 9(5), 1–22.
Bates, J., Polak, J., Jones, P., and Cook, A. (2001). “The valuation of reliability for personal travel.” Transp. Res. Part E, 37(2–3), 191–229.
Bertini, R., and El-Geneidy, A. (2004). “Modeling transit trip time using archived bus dispatch system data.” J. Transp. Eng., 56–67.
BHLS (Buses with High Level of Service). (2011). “Fundamental characteristics and recommendations for decision-making and research.”, International Association of Public Transport, Molenbeek-Saint-Jean, Belgium.
Cats, O. (2013). “Multi-agent transit operations and assignment model.” Procedia Comput. Sci., 19, 809–814.
Cats, O. (2014). “Regularity-driven bus operations: Principles, implementation and business models.” Transp. Policy, 36, 223–230.
Cats, O., Larijani, A. N., Ólafsdóttir, A., Burghout, W., Andreasson, I., and Koutsopoulos, H. N. (2012). “Holding control strategies: A simulation-based evaluation and guidelines for implementation.” Transp. Res. Rec., 2274, 100–108.
Cats, O., West, J., and Eliasson, J. (2016). “A dynamic stochastic model for evaluating congestion and crowding effects in transit systems.” Transp. Res. Part B, 89, 43–57.
Chang, J., Collura, J., Dion, F., and Rakha, H. (2003). “Evaluation of service reliability impacts of traffic signal priority strategies for bus transit.” Transp. Res. Rec., 1841, 23–31.
Chirqui, C., and Robillard, P. (1975). “Common bus lines.” Transp. Sci., 9, 115–121.
Cortes, C. E., Pages, L., and Jayakrishnan, R. (2005). “Microsimulation of flexible transit system designs in realistic urban networks.” Transp. Res. Rec., 1923, 153–163.
Diab, E. I., and El-Geneidy, A. M. (2013). “Variation in bus transit service: Understanding the impacts of various improvement strategies on transit service reliability.” Pub. Transp., 4(3), 209–231.
Ding, Y., Chien, S., and Zayas, A. (2001). “Simulating bus operations with enhanced corridor simulator.” Transp. Res. Rec., 1731, 104–111.
Dueker, K. J., Kimpel, T. J., Strathman, J. G., and Callas, S. (2004). “Determinants of bus dwell time.” J. Pub. Transp. 7(1), 21–40.
Fadaei, M., and Cats, O. (2016). “Evaluating the impacts and benefits of public transport design and operational measures.” Transp. Policy, 48, 105–116.
Fernandez, R. (2010). “Modelling public transport stops by microscopic simulation.” Transp. Res. Part C, 18(6), 856–868.
Fernández, R., Zegers, P., Weber, G., and Tyler, N. (2010). “Influence of platform height, door width, and fare collection on bus dwell time.” Transp. Res. Rec., 2143, 59–66.
Furth, P. G., and Muller, T. H. J. (2010). “Conditional bus priority at signalized intersections: Better service with less traffic disruption.” Transp. Res. Rec., 1731, 23–30.
Gao, W., Balmer, M., and Miller, E. J. (2010). “Comparisons between MATSim and EMME/2 on the Greater Toronto and Hamilton area network.” Transp. Res. Rec., 2197, 118–128.
Jenelius, E., and Cats, O. (2015). “The value of new public transport links for network robustness and redundancy.” Transportmetrica A: Transp. Sci., 11(9), 819–835.
Kittelson & Associates, Parsons Brinkkerhoff, KFH Group, and Texas A&M Transportation Institute. (2013). Transit capacity and quality of service manual, 2nd Ed., Transit Cooperative Research Program, Washington, DC.
Lee, J., Shalaby, A., Greenough, J., Bowie, M., and Hung, S. (2005). “Advanced transit signal priority control using on-line microsimulation-based transit prediction model.” Transp. Res. Rec., 1925.
Lin, W. H., and Bertini, R. (2004). “Modeling schedule recovery processes in transit operations for bus arrival time predictions.” J. Adv. Transp., 34(3), 347–365.
Meignan, D., Simonin, O., and Koukam, A. (2007). “Simulation and evaluation of urban bus-networks using a multiagent approach.” Simul. Model. Pract. Theory, 15(6), 659–671.
Milkovits, M. (2008). “Modeling the factors affecting bus stop dwell time—Use of automatic passenger counting, automatic fare counting, and automatic vehicle location data.” Transp. Res. Rec., 2072, 125–130.
Morgan, D. J. (2002). “A microscopic simulation laboratory for advanced public transport system evaluation.” Master thesis, Massachusetts Institute of Technology, Cambridge, MA.
Nesheli, M. M., and Ceder, A. (2015). “A robust, tactic-based, real-time framework for public-transport transfer synchronization.” Transp. Res. Part C: Emerging Technol., 60, 105–123.
Nesheli, M. M., Ceder, A., and Gonzalez, V. A. (2016). “Real-time public transport operational tactics using synchronized transfers to eliminate vehicle bunching.” IEEE Trans. Intell. Transp. Syst., 17(11), 3220–3229.
Neves, J. (2006). “The impact of bus lanes on urban traffic environment.” Master thesis, Dept. of Civil Engineering, Univ. of Porto, Porto, Portugal.
Osuna, E. E., and Newell, G. F. (1972). “Control strategies for an idealized public transport system.” Transp. Sci., 6(1), 52–72.
Schwartz, S. I., Hollander, A., Louie, C., and Amoruso, R. (1982). “Madison Avenue dual width bus lane project.” 61st Annual Meeting, Transportation Research Board, National Research Council, Washington, DC, 70–77.
Shalaby, A. (1999). “Simulating performance impacts of bus lanes and supporting measures.” J. Transp. Eng., 390–397.
Shalaby, A., and Soberman, R. (1994). “Effect of with-flow bus lanes on bus travel times.” Transp. Res. Rec., 1433, 24–30.
Sundberg, J., and Peterson, B. (1989). Kapacitet i kollektiva trafiksystem—Del 3—Uppehåll vid hållplats, KTH Royal Institute of Technology, Stockholm, Sweden.
Tirachini, A. (2011). “Bus dwell time: The effect of different fare collection systems, bus floor level and age of passengers.” Transportmetrica, 9(1), 28–49.
Toledo, T., Cats, O., Burghout, W., and Koutsopoulos, H. N. (2010). “Mesoscopic simulation for transit operations.” Transp. Res. Part C, 18(6), 896–908.
Turnquist, M. A. (1981). “Strategies for improving reliability of bus transit service.” Transp. Res. Rec., 818, 7–13.
van Oort, N., and van Nes, R. (2009). “Regularity analysis for optimizing urban transit network design.” Pub. Transp., 1(2), 155–168.
van Oort, N., Wilson, N. H. M., and van Nes, R. (2010). “Reliability improvement in short headway transit services: Schedule- and headway-based holding strategies.” Transp. Res. Rec., 2143, 67–76.
Vuchic, V. R. (1969). “Propagation of schedule disturbances in line-haul passenger transportation.” Revue de l’UITP, 281–284.
Vuchic, V. R. (1981). Urban public transportation systems and technology, Prentice Hall, Englewood Cliffs, NJ.
Wahba, M., and Shalaby, A. (2011). “Large-scale application of MILATRAS: Case study of the Toronto transit network.” Transportation, 38(6), 889–908.
Wardman, M., and Whelan, G. (2011). “Twenty years of rail crowding valuation studies: Evidence from lessons from British experience.” Transp. Rev., 31(3), 379–398.
Weidmann, U. (1994). “Der Fahrgastwechsel im öffentlichen Personenverkehr.”, Zürich, Switzerland.
West, J. (2011). “Boarding and bunching: The impact of boarding procedure on bus regularity and performance.” Master’s thesis, KTH Royal Institute of Technology, Stockholm, Sweden.

Information & Authors

Information

Published In

Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 143Issue 12December 2017

History

Received: Mar 10, 2015
Accepted: Jun 12, 2017
Published online: Oct 4, 2017
Published in print: Dec 1, 2017
Discussion open until: Mar 4, 2018

Permissions

Request permissions for this article.

Authors

Affiliations

Jens West, Ph.D. [email protected]
Dept. of Transport Science, KTH Royal Institute of Technology, Teknikringen 10, 100 44 Stockholm, Sweden (corresponding author). E-mail: [email protected]
Assistant Professor, Dept. of Transport and Planning, Delft Univ. of Technology, 2628 Delft, Netherlands; Dept. of Transport Science, KTH Royal Institute of Technology, Teknikringen 10, 100 44 Stockholm, Sweden. E-mail: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share