Skip to main content

Advertisement

SpringerLink
Log in

Assessment of Transit Accessibility Through Feeder Modes and Its Influence on Feeder Mode Choice Behavior

  • Research Article-Civil Engineering
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

The first and last mile connectivity is the weakest element for any public transit system becoming successful. Huge investment in provision of mass transit is not justified when these services remain underused. The present study aims to determine accessibility to metro by feeder modes and its influence on feeder mode choice behavior. An accessibility index is estimated considering trip characteristics and built environment factors. Analytic Hierarchy Process is used to determine the weights of indicators. Mode choice analysis using nested logit model shows that accessibility has considerable impact on feeder mode choice behavior of people. Further, elasticity analysis is done to estimate the percentage change in the probability of selecting a mode with reference to the change in accessibility. Findings of the study can be useful for policy-makers and transport planners for improving service quality of existing feeder services and establishing efficient feeder system that promote the use of public transit.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Chandra, S.; et al.: Accessibility evaluations of feeder transit services. Transp. Res. A Policy Pract. 52, 47–63 (2013)

    Google Scholar 

  2. Murray, A.T.; et al.: Public transportation access. Transp. Res. D Transp. Environ. 3(5), 319–328 (1998)

    Google Scholar 

  3. Brons, M.; Givoni, M.; Rietveld, P.: Access to railway stations and its potential in increasing rail use. Transp. Res. A Policy Pract. 43(2), 136–149 (2009)

    Google Scholar 

  4. Li, L.; et al.: Two dimensional accessibility analysis of metro stations in Xi’an, China. Transp. Res. A Policy Pract. 106, 414–426 (2017)

    Google Scholar 

  5. Smith, M.E.: Moving towards a greener future: an investigation of how transit-oriented development has the potential to redefine cities around sustainability. Scripps Senior theses, Claremont Graduate University, p. 81 (2015)

  6. Advani, M.: Demand estimation for public transport system: a case study of Delhi. PhD Thesis, Department of Civil Engineering, IIT Delhi (2010)

  7. Savigear, F.: A quantitative measure of accessibility. Town Plan. Rev. 38(1), 64 (1967)

    Google Scholar 

  8. Hansen, W.G.: How accessibility shapes land use. J. Am. Inst. Plan. 25(2), 73–76 (1959)

    Google Scholar 

  9. Wachs, M.; Kumagai, T.G.: Physical accessibility as a social indicator. Soc. Econ. Plan. Sci. 7(5), 437–456 (1973)

    Google Scholar 

  10. Leonardi, G.: Optimum facility location by accessibility maximizing. Environ. Plan. A 10(11), 1287–1305 (1978)

    Google Scholar 

  11. Gutiérrez, J.; Urbano, P.: Accessibility in the European Union: the impact of the trans-European road network. J. Trans. Geogr. 4(1), 15–25 (1996)

    Google Scholar 

  12. Geurs, K.T.; Van Wee, B.: Accessibility evaluation of land-use and transport strategies: review and research directions. J. Transp. Geogr. 12(2), 127–140 (2004)

    Google Scholar 

  13. El-Geneidy, A.M.; Levinson, D.M.: Access to destinations: development of accessibility measures. University of Minnesota, Minneapolis (2006)

    Google Scholar 

  14. Vickerman, R.W.: Accessibility, attraction, and potential: a review of some concepts and their use in determining mobility. Environ. Plan. A 6(6), 675–691 (1974)

    Google Scholar 

  15. Schoon, J.G.; McDonald, M.; Lee, A.: Accessibility indices: pilot study and potential use in strategic planning. Transp. Res. Rec. 1685(1), 29–38 (1999)

    Google Scholar 

  16. Polzin, S.E.; Pendyala, R.M.; Navari, S.: Development of time-of-day–based transit accessibility analysis tool. Trans. Res. Rec. 1799(1), 35–41 (2002)

    Google Scholar 

  17. TCRP and Kittelson & Associates, Inc. TCRP Web Document 6: Transit Capacity and Quality of Service Manual. Project A-15, Contractor Final Report. TRB, National Research Council, Washington, D.C., January 1999

  18. TCRP and Kittelson & Associates, Inc. Quality of Service Methods. In: Transit Capacity and Quality of Service Manual. Project A-15, Contractor Final Report. TRB, National Research Council, Washington D.C., January 1999

  19. Girao, R.; Aquino, P.W.A.D.; Fernandes, P.J.F.: Accessibility index elaboration by network geospatial analysis. Mercator (Fortaleza) 16, 1–20 (2017)

    Google Scholar 

  20. Lyu, G.; Bertolini, L.; Pfeffer, K.: How does transit-oriented development contribute to station area accessibility? A study in Beijing. Int. J. Sustain. Transp. 14, 1–11 (2019)

    Google Scholar 

  21. Bocarejo, J.P.; et al.: Accessibility analysis of the integrated transit system of Bogotá. Int. J. Sustain. Transp. 10(4), 308–320 (2016)

    Google Scholar 

  22. Rood, T.; Sprowls, S.: The local index of transit availability: An implementation manual. Local Government Commission, New Zealand (1998)

    Google Scholar 

  23. Irvin, K.: How far, by which route and why? A spatial analysis of pedestrian preference. J. Urban Des. 13(1), 81–98 (2008)

    Google Scholar 

  24. Chen, Y.; He, N.: Analysis of walkable environment and influential factors in rail transit station areas: case study of 12 neighborhoods in Shanghai. In: Urban Planning Forum 6, 96–104 (2012)

  25. Bivina, G.; Gupta, A.; Parida, M.: Influence of microscale environmental factors on perceived walk accessibility to metro stations. Transp. Res. D Transp. Environ. 67, 142–155 (2019)

    Google Scholar 

  26. Bivina, G.R.; Parida, M.: Modelling perceived pedestrian level of service of sidewalks: a structural equation approach. Transp. 34(3), 339–350 (2019). https://doi.org/10.3846/transport.2019.9819

    Article  Google Scholar 

  27. Zuo, T.; Wei, H.; Rohne, A.: Determining transit service coverage by non-motorized accessibility to transit: case study of applying GPS data in Cincinnati metropolitan area. J. Transp. Geogr. 67, 1–11 (2018)

    Google Scholar 

  28. Ryan, M.; et al.: Comparison of perceived and measured accessibility between different age groups and travel modes at Greenwood Station, Perth, Australia. Eur. J. Transp. Infrastruct. Res. 16(2), 406–423 (2016)

    Google Scholar 

  29. Krygsman, S.; Dijst, M.; Arentze, T.: Multimodal public transport: an analysis of travel time elements and the interconnectivity ratio. Transp. Policy 11(3), 265–275 (2004)

    Google Scholar 

  30. Cervero, R.: Walk-and-ride: factors influencing pedestrian access to transit. J. Public Transp. 3(4), 1–23 (2001)

    Google Scholar 

  31. Tilahun, N.; et al.: Transit use and the work commute: Analyzing the role of last mile issues. J. Transp. Geogr. 54, 359–368 (2016)

    Google Scholar 

  32. Moyano, A.; Moya-Gómez, B.; Gutiérrez, J.: Access and egress times to high-speed rail stations: a spatiotemporal accessibility analysis. J. Transp. Geogr. 73, 84–93 (2018)

    Google Scholar 

  33. Boarnet, M.G.; et al.: First/last mile transit access as an equity planning issue. Transp. Res. A Policy Pract. 103, 296–310 (2017)

    Google Scholar 

  34. Yang, M.; et al.: Metro commuters’ satisfaction in multi-type access and egress transferring groups. Transp. Res. D Transp. Environ. 34, 179–194 (2015)

    Google Scholar 

  35. Clifton, K.; Muhs, C.D.: Capturing and representing multimodal trips in travel surveys: review of the practice. Transp. Res. Rec. 2285(1), 74–83 (2012)

    Google Scholar 

  36. Debrezion, G.; Pels, E.; Rietveld, P.: Modelling the joint access mode and railway station choice. Transp. Res. E Log. Transp. Rev. 45(1), 270–283 (2009)

    Google Scholar 

  37. Sohn, K.; Shim, H.: Factors generating boardings at metro stations in the Seoul metropolitan area. Cities 27(5), 358–368 (2010)

    Google Scholar 

  38. Meng, M.; Koh, P.P.; Wong, Y.D.: Influence of socio-demography and operating streetscape on last-mile mode choice. J. Public Transp. 19(2), 3 (2016)

    Google Scholar 

  39. Hine, J.; Scott, J.: Seamless, accessible travel: users’ views of the public transport journey and interchange. Transp. Policy 7(3), 217–226 (2000)

    Google Scholar 

  40. Kuby, M.; Barranda, A.; Upchurch, C.: Factors influencing light-rail station boardings in the United States. Transp. Res. A Policy Pract. 38(3), 223–247 (2004)

    Google Scholar 

  41. Guo, Z.; Wilson, N.H.: Assessing the cost of transfer inconvenience in public transport systems: a case study of the London Underground. Transp. Res. A Policy Pract. 45(2), 91–104 (2011)

    Google Scholar 

  42. Kim, S.; Ulfarsson, G.F.: Curbing automobile use for sustainable transportation: analysis of mode choice on short home-based trips. Transportation 35(6), 723–737 (2008)

    Google Scholar 

  43. Givoni, M.; Rietveld, P.: The access journey to the railway station and its role in passengers’ satisfaction with rail travel. Transp. Policy 14(5), 357–365 (2007)

    Google Scholar 

  44. Martens, K.: The bicycle as a feedering mode: experiences from three European countries. Transp. Res. D Transp. Environ. 9(4), 281–294 (2004)

    Google Scholar 

  45. Fan, A.; Chen, X.; Wan, T.: How have travelers changed mode choices for first/last mile trips after the introduction of bicycle-sharing systems: an empirical study in Beijing, China. J. Adv. Transp. Article ID 5426080, 1–16 (2019)

  46. Hillman, R.; Pool, R.: GIS-based innovations for modelling public transport accessibility. Traffic Eng. Control 38, 554–559 (1997)

    Google Scholar 

  47. Das, D.; Ali, M.: Level of service for on-street parking. KSCE J. Civil Eng. 22(1), 330–340 (2018)

    Google Scholar 

  48. Parmar, J.; Das, P.; Dave, S.M.: Study on demand and characteristics of parking system in urban areas: a review. J. Traffic Transp. Eng. 7(1), 111–124 (2020)

    Google Scholar 

  49. Hassan, M.N.; Hawas, Y.; Kamran, A.: A multi-dimensional framework for evaluating the transit service performance. Transp. Res. A Policy Pract. 50, 47–61 (2013)

    Google Scholar 

  50. Tzeng, G.-H.; Huang, J.-J.: Introduction. In: Multiple attribute decision making: methods and applications. Chapman and Hall/CRC: London. p. 1–12 (2011)

  51. Saaty, T.L.; Vargas, L.G.: Estimating technological coefficients by the analytic hierarchy process. Soc. Econ. Plan. Sci. 13(6), 333–336 (1979)

    Google Scholar 

  52. Postorino, M.; Fedele, V.: The analytic hierarchy process to evaluate the quality of service in transit systems. WIT Trans. Built Environ. 89, 775–784 (2006)

    Google Scholar 

  53. Pogarčić, I.; Frančić, M.; Davidović, V.: Application of AHP method in traffic planning. In: Proceedigns of the 16th international symposium on electronics in traffic (2008)

  54. Oswald Beiler, M.R.; Phillips, B.: Prioritizing pedestrian corridors using walkability performance metrics and decision analysis. J. Urban Plan. Develop. 142(1), 04015009 (2015)

    Google Scholar 

  55. Train, K.E.: Chapter 4 GEV. In: Discrete choice methods with simulation, pp. 87–110. Cambridge University Press: Cambridge (2009)

    MATH  Google Scholar 

  56. McFadden, D.: Conditional logit analysis of qualitative choice behavior (1973). https://eml.berkeley.edu/reprints/mcfadden/zarembka.pdf

  57. Yan, X.; Levine, J.; Marans, R.: The effectiveness of parking policies to reduce parking demand pressure and car use. Transp. Policy 73, 41–50 (2019)

    Google Scholar 

  58. Delhi Statistical Handbook. Directorate of Economics and Statistics, Delhi (2017)

  59. Minal, S.; Chalumuri, R.S.: Commuter’s sensitivity in mode choice: an empirical study of New Delhi. J. Transp. Geogr. 100(57), 207–217 (2016)

    Google Scholar 

  60. Transport demand forecast study and development of an integrated road cum multimodal public transport network for NCT of Delhi. Transport Department, Government of National Capital Territory of Delhi (2010)

  61. Tiwari, G.: Metro rail and the city: derailing public transport. Econ. Polit. Weekly 48, 65–76 (2013)

    Google Scholar 

  62. Goel, R.; Tiwari, G.: Access–egress and other travel characteristics of metro users in Delhi and its satellite cities. IATSS Res. 39(2), 164–172 (2016)

    Google Scholar 

  63. Dalvi, M.Q.; Martin, K.: The measurement of accessibility: some preliminary results. Transportation 5(1), 17–42 (1976)

    Google Scholar 

  64. Hu, H.; et al.: Travel mode choices in small cities of China: A case study of Changting. Transp. Res. D Transp. Environ. 59, 361–374 (2018)

    Google Scholar 

  65. Rodrı́guez, D.A.; Joo, J.: The relationship between non-motorized mode choice and the local physical environment. Transp. Res. D Transp. Environ. 9(2): 151–173 (2004)

  66. Ashalatha, R.; Manju, V.; Zacharia, A.B.: Mode choice behavior of commuters in Thiruvananthapuram City. J. Transp. Eng. 139(5), 494–502 (2012)

    Google Scholar 

  67. Hensher, D.A.; Rose, J.M.: Development of commuter and non-commuter mode choice models for the assessment of new public transport infrastructure projects: a case study. Transp. Res. A Policy Pract. 41(5), 428–443 (2007)

    Google Scholar 

  68. Zhao, R.; et al.: Consumers’ perception, purchase intention, and willingness to pay for carbon-labeled products: A case study of Chengdu in China. J. Clean. Prod. 171, 1664–1671 (2018)

    Google Scholar 

  69. Song, Y.; et al.: New walking and cycling infrastructure and modal shift in the UK: a quasi-experimental panel study. Transp. Res. A Policy Pract. 95, 320–333 (2017)

    Google Scholar 

  70. Brög, W.; et al.: Evaluation of voluntary travel behaviour change: experiences from three continents. Transp. Policy 16(6), 281–292 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Civil Engineering Department, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat, 390001, India

    Gulnazbanu Saiyad & Dipak Rathwa

  2. Transport Planning and Environment Division, CSIR- Central Road Research Institute, Delhi-Mathura Road, New Delhi, 110025, India

    Minal Srivastava

Authors
  1. Gulnazbanu Saiyad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Minal Srivastava
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dipak Rathwa
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Saiyad, G., Srivastava, M. & Rathwa, D. Assessment of Transit Accessibility Through Feeder Modes and Its Influence on Feeder Mode Choice Behavior. Arab J Sci Eng 47, 4483–4497 (2022). https://doi.org/10.1007/s13369-021-06082-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-021-06082-9

Keywords

Search

Navigation