Planning a high-frequency transfer-based bus network: How do we get there?

Emily Grise

Anson Stewart

Ahmed El-Geneidy

DOI: https://doi.org/10.5198/jtlu.2021.1742

Keywords: Public transport, bus network planning, bus network redesign, direct-service bus network


Abstract

As cities have grown more dispersed and auto-oriented, demand for travel has become increasingly difficult to meet via public transit. Public transit ridership, particularly bus ridership, has recently been on the decline in many urban areas in Canada and the United States, and many agencies have either undergone or are planning comprehensive bus network redesigns in response. While comprehensive bus network redesigns are not novel to public transit, network redesigns are commonly being considered in cities to optimize operational costs and reverse downward trends in transit ridership. For cities considering a comprehensive bus network redesign, there is currently no comprehensive easy-to-follow planning process available to guide cities through such a major undertaking. In light of that, this study presents a methodology to guide transport professionals through the planning process of a bus network redesign, using Longueuil, Quebec, as a case study. Currently, Longueuil operates a door-to-door network, and the goal is to move to a transfer-based, high-frequency service while keeping the existing number of buses constant. A variety of data sources that capture regional travel behavior and network performance are overlaid using a GIS-based grid-cell model to identify priority bus corridors. A series of analyses to measure and quantify anticipated and actual improvements from the proposed bus network redesign are conducted, including coverage analysis, change in accessibility to jobs, and travel time analysis. Accessibility to jobs was the key performance measure used in this analysis and is presented as a useful tool for planners and transit agencies to obtain buy-in for the proposed plan. This methodology provides transport professionals with a flexible and reproducible guide to consider when conducting a bus network redesign, while ensuring that such a network overhaul maximizes the number of opportunities that residents can access by transit and does not add an additional burden to an agency’s operating budget.


References

Agence Métropolitaine de Transport. (2013). Enquête origine-destination 2013. Montreal: Agence Métropolitaine de Transport.

Allen, J., Muñoz, J., & Rosell, J. (2019). Effect of a major network reform on bus transit satisfaction. Transportation Research Part A: Policy and Practice, 124, 310–333.

Badia, H., Argote-Cabanero, J., & Daganzo, C. (2017). How network structure can boost and shape the demand for bus transit. Transportation Research Part A: Policy and Practice, 103, 83–94.

Badia, H., Estrada, M., & Robusté, F. (2014). Competitive transit network design in cities with radial street patterns. Transportation Research Part B: Methodological, 59, 161–181.

Badia, H., Estrada, M., & Robusté, F. (2016). Bus network structure and mobility pattern: A monocentric analytical approach on a grid street layout. Transportation Research Part B: Methodological, 93, 37–56.

Banister, D. (2008). The sustainable mobility paradigm. Transport Policy, 15(2), 73–80. http://ac.els-cdn.com/S0967070X07000820/1-s2.0-S0967070X07000820-main.pdf?_tid=6cf470aa-187e-11e6-9112-00000aab0f27&acdnat=1463084375_fafb4bd6b84b7861ae745255d646ff71

Ben-Akiva, M., & Morikawa, T. (2002). Comparing ridership attraction of rail and bus. Transport Policy, 9(2), 107–116.

Bhattacharya, T., Brown, J., Jaroszynski, M., & Batuhan, T. (2014). The effects of perception vs.“reality” on travel behavior after a major transit service change: The case of Tallahassee, Florida. Journal of Public Transportation, 17(2), 1–26.

Boisjoly, G., & El-Geneidy, A. (2016). Daily fluctuations in transit and job availability: A comparative assessment of time-sensitive accessibility measures. Journal of Transport Geography, 52, 73–81.

Boisjoly, G., Grisé, E., Maguire, M., Veillette, M., Deboosere, R., Berrebi, E., & El-Geneidy, A. (2018). Invest in the ride: A 14 year longitudinal analysis of the determinants of public transport ridership in 25 North American cities. Transport Research Part A: Policy and Practice, 116, 434–445.

Brown, J., & Thompson, G. (2008). Examining the influence of multidestination service orientation on transit service productivity: A multivariate analysis. Transportation, 35(2), 237–252.

Cui, B., & El-Geneidy, A. (2019). Accessibility, equity, and mode share: A comparative analysis across 11 Canadian metropolitan areas. Transport Findings, February. https://doi.org/10.32866/7400

Daganzo, C. (1987). The break-bulk role of terminals in many-to-many logistic networks. Operations Research, 35(4), 543–555.

Daganzo, C. (2010). Structure of competitive transit networks. Transportation Research Part B: Methodological, 44(4), 434–446.

Dell’Olio, L., Ibeas, A., & Cecin, P. (2011). The quality of service desired by public transport users. Transport Policy, 18(1), 217–227.

Dill, J., Schlossberg, M., Ma, L., & Meyer, C. (2013). Predicting transit ridership at the stop level: The role of service and urban form. Paper presented at the 92nd annual meeting of the Transportation Research Board, Washington, DC.

El-Geneidy, A., Grimsrud, M., Wasfi, R., Tétreault, P., & Surprenant-Legault, J. (2014). New evidence on walking distances to transit stops: Identifying redundancies and gaps using variable service areas. Transportation, 41(1), 193–210.

Estrada, M., Roca-Riu, M., Badia, H., Robusté, F., & Daganzo, C. (2011). Design and implementation of efficient transit networks: Procedure, case study and validity test. Transportation Research Part A: Policy and Practice, 17, 113–135.

Grisé, E., & El-Geneidy, A. (2018). If we build it, who will benefit? A multi-criteria approach for the prioritization of new bicycle lanes in Quebec City, Canada. Journal of Transport and Land Use, 11(1), 217–235.

Gutiérrez, J., & García-Palomares, J. (2008). Distance-measure impacts on the calculation of transport service areas using GIS. Environment and Planning B: Planning and Design, 35, 480–503.

Handy, S., & Niemeier, D. (1997). Measuring accessibility: An exploration of issues and alternatives. Environment and planning A, 29(7), 1175–1194.

Hansen, W. (1959). How accessibility shapes land use. Journal of the American Institute of Planners, 25(2), 73–76.

Hsiao, S., Lu, J., Sterling, J., & Weatherford, M. (1997). Use of geographic information system for analysis of transit pedestrian access. Transportation Research Record: Journal of the Transportation Research Board, 1604, 50–59.

Kalantari, N., Zamanian, M., & Amiripour, S. (2014). Bus network modification problem: A new approach to bus network design. Paper presented at the Transportation Research Board, Washington, DC.

Kimpel, T., Dueker, K., & El-Geneidy, A. (2007). Using GIS to measure the effect of overlapping service areas on passenger boardings at bus stops. Urban and Regional Information Systems Association Journal, 19(1), 5–11.

Larsen, J., Patterson, Z., & El-Geneidy, A. (2013). Build it. But where? The use of geographic information systems in identifying locations for new cycling infrastructure. International Journal of Sustainable Transportation, 7(4), 299–317.

Mouwen, A. (2015). Drivers of customer satisfaction with public transport services. Transportation research Part A: Policy and Practice, 78, 1–20.

National Academies of Sciences, Engineering, and Medicine. (2019). Comprehensive bus network redesigns. Washington, DC: National Academies of Sciences, Engeneering, and Medicine.

National Academies of Sciences, Engineering, and Medicine. (2020). Analysis of recent public transit ridership trends. Washington, DC: National Academies of Sciences, Engineering, and Medicine.

O'Neill, W., Ramsey, R., & Chou, J. (1992). Analysis of transit service areas using Geographic Information Systems. Transportation Research Record: Journal of the Transportation Research Board, 1364, 131–138.

Owen, A., & Levinson, D. (2015). Modeling the commute mode share of transit using continuous accessibility to jobs. Transportation research Part A: Policy and Practice, 74, 110–122.

RTL. (2017). Annual report. Retrieved from http://www.rtl-longueuil.qc.ca/en-CA/press-room/documents-and-practical-information/annual-reports/

RTL. (2019). About. Retrieved from http://m.rtl-longueuil.qc.ca/en-CA/rtl/about

Statistics Canada. (2016). 2016 Census profile of census subdivisions. Retrieved from http://datacentre.chass.utoronto.ca/cgi-bin/census/2016/displayCensus.cgi?year=2016&geo=csd

Straatemeier, T. (2008). How to plan for regional accessibility? Transport Policy, 15(2), 127–137.

Susilo, Y., & Cats, O. (2014). Exploring key determinants of travel satisfaction for multi-modal trips by different traveler groups. Transportation Research Part A: Policy and Practice, 67, 366–380.

Thompson, G. (1977). Planning considerations for alternative transit route structures. Journal of the American Planning Association, 43(2), 158–168.

Thompson, G., & Matoff, T. (2003). Keeping up with Joneses: Radical vs. multidestinational transit in decentralizing regions. Journal of the American Planning Association, 69(3), 296.

Trapote-Barreira, C., Robusté, F., Badia-Rodríguez, H., & Estrada-Romeu, M. (2016). Learnings from urban bus network change. Paper presented at the Transportation Research Board, Washington, DC.

Vuchic, V. (2005). Urban transit: Operations, planning, and economics. Hoboken, NJ: John Wiley & Sons.

Zhao, F., Chow, L., Li, M., Ubaka, I., & Gan, A. (2003). Forecasting transit walk accessibility: Regression model alternative to buffer method. Transportation Research Record: Journal of the Transportation Research Board, 1835, 34–41.