Abstract
This paper proposes a novel framework to identify the most informative variables for clustering bus priority corridors according to their similarities regarding system and operational aspects. Although each bus corridor has its peculiarities, understanding the similarities (e.g., system, physical and operational aspects) between corridors of different regions of the world can help researchers and transit specialists to draw up strategies tailored to improving the traffic in the cities. For that matter, we integrate a novel metric for measuring clustering quality to the omit-one-variable-out-at-a-time selection procedure. The proposed method relies on three steps: (i) collect and preprocess data describing bus corridors; (ii) define the number of clusters to be generated based on a hierarchical approach; and (iii) iteratively group bus corridors, and eliminate less relevant clustering variables. When applied to a dataset comprised of 296 bus priority corridors from 45 countries and described by 44 variables, the proposed framework retained only four variables (i.e., brand and/or logo, station spacing, enhanced stations, and operating speed) responsible for the best stratification of corridors. Four clusters were formed and qualitatively assessed regarding their similarities in terms of system, physical and operational aspects. Corridors were grouped into basic corridors (cluster 1), improved corridors (cluster 2), Bus Rapid Transit (BRT) and Bus with High Level of Service (BHLS) systems (cluster 3), and express, limited-stop services (cluster 4).
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References
Anzanello MJ, Fogliatto FS (2011) Selecting the best clustering variables for grouping mass-customized products involving workers’ learning. Int J Prod Econ 130(2):268–276. https://doi.org/10.1016/j.ijpe.2011.01.009
Anzanello MJ, Fogliatto FS, Ortiz RS, Limberger R, Mariotti K (2014) Selecting relevant Fourier transform infrared spectroscopy wavenumbers for clustering authentic and counterfeit drug samples. Sci Just 54(5):363–368. https://doi.org/10.1016/j.scijus.2014.04.005
Basso LJ, Guevara CA, Gschwender A, Fuster M (2011) Congestion pricing, transit subsidies and dedicated bus lanes: efficient and practical solutions to congestion. Transport Policy 18(5):676–684. https://doi.org/10.1016/j.tranpol.2011.01.002
Ben-Dor G, Ben-Elia E, Benenson I (2018) Assessing the impacts of dedicated bus lanes on urban traffic congestion and modal split with an agent-based model. Procedia Comput Sci 130:824–829. https://doi.org/10.1016/j.procs.2018.04.071
Cain A, Flynn J (2013) Examining the ridership attraction potential of bus rapid transit: a quantitative analysis of image and perception. J Public Transport 16(4):63–82. https://doi.org/10.5038/2375-0901.16.4.4
Cain A, Flynn J, McCourt M, Reyes T (2009) Quantifying the importance of image and perception to Bus Rapid Transit. No. FTA-FL-26–7109.2009. 3. https://trid.trb.org/view/889573. Accessed 24 May 2017
Carrigan A, King R, Velasquez JM, Raifman M, Duduta N (2013) Social, environmental and economic impacts of BRT systems. Bus Rapid Transit Case Studies from Around the World. World Resources Institute, Embarq. https://www.wrirosscities.org/sites/default/files/Social-Environmental-Economic-Impacts-BRT-Bus-Rapid-Transit-EMBARQ.pdf. Accessed 24 May 2017
Chiabaut N, Küng M, Menendez M, Leclercq L (2018) Perimeter control as an alternative to dedicated bus lanes: a case study. Transp Res Rec 2672(20):110–120. https://doi.org/10.1177/0361198118786607
Chiabaut N, Barcet A (2019) Demonstration and evaluation of intermittent bus lane strategy. Public Transp 11:443–456. https://doi.org/10.1007/s12469-019-00210-3
Combs TS, Rodríguez DA (2014) Joint impacts of bus rapid transit and urban form on vehicle ownership: new evidence from a quasi-longitudinal analysis in Bogotá, Colombia. Transp Res Part A Policy Pract 69:272–285. https://doi.org/10.1016/j.tra.2014.08.025
Deng T, Ma M, Wang J (2013) Evaluation of bus rapid transit implementation in China: current performance and progress. J Urban Plan Dev 1393:226–234. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000150
Eichler M, Daganzo CF (2006) Bus lanes with intermittent priority: strategy formulae and an evaluation. Transp Res Part B Methodol 40(9):731–744. https://doi.org/10.1016/j.trb.2005.10.001
Everitt BS, Landau S, Leese M, Stahl D (2011) Cluster analysis. Wiley, Chichester
Gao S, Li G, Wang D (2005) A new approach for detecting multivariate outliers. Commun Stat Theory Methods 34.8:1857–1865. https://doi.org/10.1081/STA-200066315
Hair Jr, JF, Anderson RE, Tatham RL, Black WC (1995) Multivariate data analysis: with readings. Prentice-Hall, Inc. ISBN: 978-0-02-349020-0
Härdle WK, Simar L (2012) Applied multivariate statistical analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-030-26006-4
He H, Menendez M, Ilgin Guler S (2018) Analytical evaluation of flexible-sharing strategies on multi-modal arterials. Transp Res Part A Policy Pract 114:364–379. https://doi.org/10.1016/j.tra.2018.01.038
He SX, Dong J, Liang SD, Yuan PC (2019) An approach to improve the operational stability of a bus line by adjusting bus speeds on the dedicated bus lanes. Transp Res Part C Emerg Technol 107:54–69. https://doi.org/10.1016/j.trc.2019.08.001
Heddebaut O, Finn B, Rabuel S, Rambaud F (2010) The European bus with a high level of service (BHLS): concept and practice. Built Environ 36(3):307–316. https://doi.org/10.2148/benv.36.3.307
Hensher DA, Golob TF (2008) Bus rapid transit systems: a comparative assessment. Transportation 35(4):501–518. https://doi.org/10.1007/s11116-008-9163-y
Hensher DA, Li Z (2012) Ridership drivers of bus rapid transit systems. Transportation 39(6):1209–1221. https://doi.org/10.1007/s11116-012-9392-y
Hidalgo D, Gutiérrez L (2013) BRT and BHLS around the world: explosive growth, large positive impacts and many issues outstanding. Res Transport Econ 39.1:8–13. https://doi.org/10.1016/j.retrec.2012.05.018
Hidalgo D, Muñoz JC (2014) A review of technological improvements in bus rapid transit (BRT) and buses with high level of service (BHLS). Public Transp 6(3):185–213. https://doi.org/10.1007/s12469-014-0089-9
ITDP: the BRT Standard 2016 Edition. Institute for Transportation and Development Policy (2016). https://www.itdp.org/2016/06/21/the-brt-standard/. Accessed 24 May 2017
Jain AK, Dubes RC (1988) Algorithms for clustering data. Prentice-Hall, Englewood Cliffs, NJ
Kannan KS, Manoj K (2015) Outlier detection in multivariate data. J Appl Math Sci 9: 2317–2324. https://doi.org/10.12988/ams.2015.53213
Kaufman L, Rousseeuw PJ (2009) Finding groups in data: an introduction to cluster analysis. Wiley, Hoboken, NJ. ISBN: 978-0-471-73578-6
Kharas H (2010) The emerging middle class in developing countries. OECD Publishing. https://www.oecd.org/development/pgd/44457738.pdf. Accessed 24 May 2017
Li J (2013) A design principle analysis of harmonious city bus station. Appl Mech Mat 253:1880–1883. https://doi.org/10.4028/www.scientific.net/AMM.253-255.1880. Accessed 24 May 2017
Linovski O, Baker DM, Manaugh K (2018) Equity in practice? Evaluations of equity in planning for bus rapid transit. Transp Res Part A Policy Pract 113:75–87. https://doi.org/10.1016/j.tra.2018.03.030
Litman T (2009) Transportation cost and benefit analysis: techniques, estimates and implications. Victoria transport policy institute, Victoria. https://www.vtpi.org/tca/tca00.pdf. Accessed 24 May 2017
Litman T (2017) Smart transportation emission reduction strategies: identifying truly optimal ways to conserve energy and reduce emissions. Victoria transport policy institute. https://www.vtpi.org/ster.pdf. Accessed 14 July 2020
Liu Y, Li Z, Xiong H, Gao X, Wu J, Wu S (2013) Understanding and enhancement of internal clustering validation measures. IEEE Trans Cybern 43(3):982–994. https://doi.org/10.1109/TSMCB.2012.2220543
Luo Y, Qian D (2018) Research on the impact scope of bus stations based on the application of bus lanes. J Adv Transport 2018:3935852. https://doi.org/10.1155/2018/3935852
Maulik U, Bandyopadhyay S (2002) Performance evaluation of some clustering algorithms and validity indices. IEEE Trans Pattern Anal Mach Intell 24(12):1650–1654. https://doi.org/10.1109/TPAMI.2002.1114856
Merkert R, Mulley C, Hakim MM (2017) Determinants of bus rapid transit (BRT) system revenue and effectiveness—a global benchmarking exercise. Transp Res Part A Policy and Pract 106:75–88. https://doi.org/10.1016/j.tra.2017.09.010
OECD/ITF (2012) Transport outlook 2012: seamless transport for greener growth. International Trans-port Forum/OECD, ITF. https://www.itf-oecd.org/sites/default/files/docs/12outlook.pdf. Accessed 24 May 2017
Pereira BM (2011) Avaliação do desempenho de configurações físicas e operacionais de sistemas BRT. LUME—Repositório digital da UFRGS. https://lume.ufrgs.br/handle/10183/28932. Accessed 24 May 2017
Poku-Boansi M, Marsden G (2018) Bus rapid transit systems as a governance reform project. J Transp Geogr 70:193–202. https://doi.org/10.1016/j.jtrangeo.2018.06.005
Rencher AC (2002) Methods of multivariate analysis, Second Edition. Wiley
Rousseeuw PJ (1987) Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J Comput Appl Math 20:53–65. https://doi.org/10.1016/0377-0427(87)90125-7
Schramm L, Watkins K, Rutherford S (2010) Variables that affect variability of travel time on bus rapid transit systems. Transp Res Rec 2143:77–84. https://doi.org/10.3141/2143-10
Tirachini A, Hensher DA (2011) Bus congestion, optimal infrastructure investment and the choice of a fare collection system in dedicated bus corridors. Transp Res Part B Methodol 45(5):828–844. https://doi.org/10.1016/j.trb.2011.02.006
United Nations. World urbanization prospects 2018: highlights. New York
Wright L, Hook W (2007) Bus rapid transit planning guide. Institute for Transportation and Development Policy, New York
Wu J, Hounsell N (1998) Bus priority using pre-signals. Transp Res Part A Policy Pract 32A(8):563–583
Yang H, Huang H-J (1999) Carpooling and congestion pricing in a multilane highway with high-occupancy-vehicle lanes. Transp Res Part A Policy Pract 332:139–155. https://doi.org/10.1016/S0965-8564(98)00035-4
Web References
ALC-BRT: methodology (2017). https://www.brt.cl/observatory/methodology/. Accessed 24 May 2017.
ALC-BRT, EMBARQ, IEA and SIBRT: Global, BRTData. (2016). https://brtdata.org/. Accessed 24 May 2020.
ITDP. The BRT Planning Guide (2017). URL https://www.itdp.org/the-brt-planning-guide/. Accessed 24 May 2020.
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Rocha, M., Silva, C.A.M., Santos Junior, R.G. et al. Selecting the most relevant variables towards clustering bus priority corridors. Public Transp 12, 587–609 (2020). https://doi.org/10.1007/s12469-020-00245-x
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DOI: https://doi.org/10.1007/s12469-020-00245-x