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An analysis of transport suitability, modal choice and trip pattern using accessibility and network approach: a study of Jamshedpur city, India

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Abstract

The transportation system is considered the most important element of urban infrastructure and therefore, contemporary urban research precise more emphasis on the well-managed sustainable transport system. Accessibility and connectivity are two important tools regarding urban mobility, trip generation and modal choice as well as transportation management. The assessment of transport suitability is now the central part of transport management. From these perspectives, this study has been focused on the patterns of urban mobility and modal choice on the basis of transport accessibility and suitability. The Jamshedpur city and five adjoining urban areas are selected for assessment. The GIS-based accessibility modeling and network analysis have been used in this study. Moreover, the empirical field survey has also been made for the assessment of trip generation in selected nodes. Therefore, the analytic hierarchy process (AHP) was applied to assess the nature and patterns of trip occurrences and content validity ratio (CVR) and consistency ratio (CR) were used for validation. Furthermore, transport suitability index (TSI) in the different traffic zones were measured. The result shows that Jamshedpur is the most suitable in existing transportation supply–demand system as well as sustainable transportation management.

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Source: RTO Sonari, Jamshedpur city, 2015

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References

  1. Rodrigue, J. P., Comtois, C., & Slack, B. (2006). The geography of transport systems. London: Routledge.

    Google Scholar 

  2. Geurs, K. T., & van Wee, B. (2004). Accessibility evaluation of land-use and transport strategies: Review and research directions. Journal of Transport Geography, 12(2), 127–140. https://doi.org/10.1016/j.jtrangeo.2003.10.005.

    Article  Google Scholar 

  3. May, A., Boehler-Baedeker, S., Delgado, L., Durlin, T., Enache, M., & van der Pas, J. W. (2017). Appropriate national policy frameworks for sustainable urban mobility plans. European Transport Research Review, 9(1), 7. https://doi.org/10.1007/s12544-017-0224-1.

    Article  Google Scholar 

  4. Taffee, E. J., & Gauthier, H. L. (1973). Geography of transportation. Upper Saddle River: Prentice-Hall.

    Google Scholar 

  5. Saxena, H. M. (2005). Transport geography. Jaipur: Rawat Publications. (ISBN 81-7033-945-6).

    Google Scholar 

  6. Dinda, S., Das, K., Chatterjee, N. D., & Ghosh, S. (2018). Integration of GIS and statistical approach in mapping of urban sprawl and predicting future growth in Midnapore town, India. Modeling Earth Systems and Environment. https://doi.org/10.1007/s40808-018-0536-8.

    Google Scholar 

  7. Thill, J. C. (Ed.). (2000). Geographical system in transportation research. Oxford: Elsevier Science.

    Google Scholar 

  8. Michael, F. (1986). Nonlinear cost network models in transportation analysis. Mathematical Programming Study, 26, 167–196.

    Article  Google Scholar 

  9. Tyrinopoulos, Y., & Antoniou, C. (2013). Factors affecting modal choice in urban mobility. European Transport Research Review, 5(1), 27–39. https://doi.org/10.1007/s12544-012-0088-3.

    Article  Google Scholar 

  10. Chen, S., Claramunt, C., & Ray, C. (2014). A spatio-temporal modelling approach for the study of the connectivity and accessibility of the Guangzhou metropolitan network. Journal of Transport Geography, 36, 12–23. https://doi.org/10.1016/j.jtrangeo.2014.02.006.

    Article  Google Scholar 

  11. Burns, R. E. (1969). Transport planning: Selection of analytical techniques. Journal of Transport Economics and Policy, 3, 306–321.

    Google Scholar 

  12. van der Waerden, P., Couwenberg, E., & Wets, G. (2018). Travelers’ preferences regarding the interior of public buses: A hierarchical information integration approach. Public Transport. https://doi.org/10.1029/GL015i006p00561.

    Google Scholar 

  13. Vandenbulcke, G., Steenberghen, T., & Thomas, I. (2009). Mapping accessibility in Belgium: A tool for land-use and transport planning? Journal of Transport Geography, 17(1), 39–53. https://doi.org/10.1016/j.jtrangeo.2008.04.008.

    Article  Google Scholar 

  14. Jayasinghe, A., Sano, K., & Nishiuchi, H. (2015). Explaining traffic flow patterns using centrality measures. International Journal for Traffic and Transport Engineering, 5(2), 134–149. https://doi.org/10.7708/ijtte.2015.5(2).05.

    Article  Google Scholar 

  15. Bikdeli, S., Shafaqi, S., & Vosouqi, F. (2017). Accessibility modeling for land use, population and public transportation in Mashhad, NE Iran. Spatial Information Research, 25(3), 481–489. https://doi.org/10.1007/s41324-017-0116-4.

    Article  Google Scholar 

  16. Black, J. A., Paez, A., & Suthanaya, P. A. (2002). Sustainable urban transportation: Performance indicators and some analytical approaches. Journal of Urban Planning and Development, 128(4), 184–209. https://doi.org/10.1061/(ASCE)0733-9488(2002)128:4(184).

    Article  Google Scholar 

  17. Richardson, B. C. (2005). Sustainable transport: Analysis frameworks. Journal of Transport Geography, 13, 29–39. https://doi.org/10.1016/j.jtrangeo.2004.11.005.

    Article  Google Scholar 

  18. Thompson, K., & Schofield, P. (2007). An investigation of the relationship between public transport performance and destination satisfaction. Journal of Transport Geography, 15(2), 136–144. https://doi.org/10.1016/j.jtrangeo.2006.11.004.

    Article  Google Scholar 

  19. Páez, A., Scott, D. M., & Morency, C. (2012). Measuring accessibility: Positive and normative implementations of various accessibility indicators. Journal of Transport Geography, 25, 141–153. https://doi.org/10.1016/j.jtrangeo.2012.03.016.

    Article  Google Scholar 

  20. Kitamura, R. (2009). A dynamic model system of household car ownership, trip generation, and modal split: Model development and simulation experiment. Transportation, 36(6), 711–732. https://doi.org/10.1007/s11116-009-9241-9.

    Article  Google Scholar 

  21. Cordera, R., Coppola, P., dell’Olio, L., & Ibeas, Á. (2016). Is accessibility relevant in trip generation? Modelling the interaction between trip generation and accessibility taking into account spatial effects. Transportation, 44(6), 1577–1603. https://doi.org/10.1007/s11116-016-9715-5.

    Article  Google Scholar 

  22. Da Silva, A. N. R., da Silva Costa, M., & Macedo, M. H. (2008). Multiple views of sustainable urban mobility: The case of Brazil. Transport Policy, 15(6), 350–360. https://doi.org/10.1016/j.tranpol.2008.12.003.

    Article  Google Scholar 

  23. Cheng, S., Xie, B., Bie, Y., Zhang, Y., & Zhang, S. (2018). Measure dynamic individual spatial-temporal accessibility by public transit: Integrating time-table and passenger departure time. Journal of Transport Geography, 66, 235–247. https://doi.org/10.1016/j.jtrangeo.2017.12.005.

    Article  Google Scholar 

  24. Zito, P., & Salvo, G. (2011). Toward an urban transport sustainability Index: An European comparison. European Transportation Research Review, 3(4), 179–195. https://doi.org/10.1007/s12544-011-0059-0.

    Article  Google Scholar 

  25. Awasthi, A., & Chauhan, S. S. (2011). Using AHP and Dempster–Shafer theory for evaluating sustainable transport solutions. Environmental Modelling and Software, 26(6), 787–796. https://doi.org/10.1016/j.envsoft.2010.11.010.

    Article  Google Scholar 

  26. Sheffi, Y. (1985). Urban transportation network equilibrium analysis with mathematical programming methods (p. 07632). Englewood: Prentice-Hall,INC.

    Google Scholar 

  27. Ford, A., Barr, S., Dawson, R., & James, P. (2015). Transport accessibility analysis using GIS: Assessing sustainable transport in London. ISPRS, International Journal of Geo-Information, 4(1), 124–149. https://doi.org/10.3390/ijgi4010124.

    Article  Google Scholar 

  28. Allsop, R. (2008). Transport network and their use: How real can modelling get? Philosophical transaction: Mathematical, Physical and Engineering Sciences. Network and Modelling and Control, 366(1872), 1879–1892. https://doi.org/10.1098/rsta.2008.0013.

    Article  Google Scholar 

  29. Delso, J., Martín, B., & Ortega, E. (2018). A new procedure using network analysis and kernel density estimations to evaluate the effect of urban configurations on pedestrian mobility. The case study of Vitoria–Gasteiz. Journal of Transport Geography, 67, 61–72. https://doi.org/10.1016/j.jtrangeo.2018.02.001.

    Article  Google Scholar 

  30. Kim, H., & Song, Y. (2018). An integrated measure of accessibility and reliability of mass transit systems. Transportation, 45(4), 1075–1100. https://doi.org/10.1007/s11116-018-9866-7.

    Article  Google Scholar 

  31. Wong, K. I., Wong, S. C., Wu, J. U., Yang, H., William, H. K., & Lam, W. H. K. (2004). A combined distribution, hierarchical mode choice, and assignment network model with multiple user and mode classes. In D. H. Lee (Ed.), Urban and regional transportation modeling (pp. 25–42). Cheltenham: Edward Elgar Publishing Limited.

    Google Scholar 

  32. Hymel, K. M., Small, K. A., & Dender, K. V. (2010). Induced demand and rebound effects in road transport. Transportation Research Part B, 44, 1220–1241. https://doi.org/10.1016/j.trb.2010.02.007.

    Article  Google Scholar 

  33. Pyrialakou, V. D., Gkritza, K., & Fricker, J. D. (2016). Accessibility, mobility, and realized travel behavior: Assessing transport disadvantage from a policy perspective. Journal of Transport Geography, 51, 252–269. https://doi.org/10.1016/j.jtrangeo.2016.02.001.

    Article  Google Scholar 

  34. Census of India. (2011a). Final population total. http://censusindia.gov.in. Accessed 12 February, 2015.

  35. Census of India. (2011b). Provisional population total. http://censusindia.gov.in. Accessed 12 February, 2015.

  36. Jamshedpur Utility and Service Company (JUSCO). (2013). Annual planning report. Jamshedpur: TATA Iron and Steel Company.

    Google Scholar 

  37. Department of Transport, Government of Jharkhand. http://www.jharkhand.gov.in/web/transport-project. Accessed on 24th January, 2018.

  38. Road and Transport Office. (2015). Vehicle registration report of 2012–2015. Jamshedpur: Sonari Road.

    Google Scholar 

  39. Transport strategy and transport modelling with PTV Visum. (2016). PTV group traffic software, UK.

  40. Feuillet, T., Commenges, H., Menai, M., Salze, P., Perchoux, C., Reuillon, R., et al. (2018). A massive geographically weighted regression model of walking-environment relationships. Journal of Transport Geography, 68, 118–129. https://doi.org/10.1016/j.jtrangeo.2018.03.002.

    Article  Google Scholar 

  41. Amaya, M., Cruzat, R., & Munizaga, M. A. (2018). Estimating the residence zone of frequent public transport users to make travel pattern and time use analysis. Journal of Transport Geography, 66, 330–339. https://doi.org/10.1016/j.jtrangeo.2017.10.017.

    Article  Google Scholar 

  42. Wolday, F., Cao, J., & Næss, P. (2018). Examining factors that keep residents with high transit preference away from transit-rich zones and associated behavior outcomes. Journal of Transport Geography, 66, 224–234. https://doi.org/10.1016/j.jtrangeo.2017.12.009.

    Article  Google Scholar 

  43. Seo, S. E., Ohmori, N., & Harata, N. (2013). Effects of household structure and accessibility on travel. Transportation, 40(4), 847–865. https://doi.org/10.1007/s11116-013-9468-3.

    Article  Google Scholar 

  44. Fox, M. (1995). Transport planning and the human activity approach. Journal of Transport Geography, 3(2), 105–116. https://doi.org/10.1016/0966-6923(95)00003-L.

    Article  Google Scholar 

  45. MacCrimmon, K. R. (1968). Decision making among multiple–attribute alternatives: A survey and consolidated approach. Arpa Order. RM-4823. Santa Monica: Rand Corporation.

  46. Hwang, C. L., & Masud, A. S. M. (1979). Multiple objective decision making: Methods and applications. Lecture Notes in Economics and Mathematical Systems, 164, 358. https://doi.org/10.1007/978-3-642-45511-7.

    Google Scholar 

  47. Keršuliene, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (Swara). Journal of Business Economics and Management, 11(2), 243–258. https://doi.org/10.3846/jbem.2010.12.

    Article  Google Scholar 

  48. Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83. https://doi.org/10.1504/IJSSCI.2008.017590.

    Article  Google Scholar 

  49. Saaty, T. L. (1988). What is the analytic hierarchy process? Mathematical Models for Decision Support, 56, 109–121. https://doi.org/10.1007/978-3-642-83555-1_5.

    Article  Google Scholar 

  50. Lawshe, C. (1975). A quantitative approach to content validity. Personnel Psychology, 1, 563–575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x.

    Article  Google Scholar 

  51. Kansky, K. J. (1963). Structure of transport networks: Relationships between network geometry and regional characteristics. Department of Geography, University of Chicago, Research Paper, 84.

  52. Ghosh, S., Dinda, S., & Chatterjee, N. D. (2017). Sustainable urban transport modelling for Jamshedpur city: A geospatial appraisal. In B. K. Ramprasad (Ed.), Geoinformatics for carto-diversity and its management (Vol. 37, pp. 30–40). Hyderabad: Indian Cartographer. (ISSN 0927-8392).

    Google Scholar 

  53. Abulibdeh, A., & Zaidan, E. (2018). Analysis of factors affecting willingness to pay for high-occupancy-toll lanes: Results from stated-preference survey of travelers. Journal of Transport Geography, 66, 91–105. https://doi.org/10.1016/j.jtrangeo.2017.11.015.

    Article  Google Scholar 

  54. Cullinane, S., & Cullinane, K. (1999). Attitudes towards traffic problems and public transport in the Dartmoor and Lake District National Parks. Journal of Transport Geography, 7(1), 79–87. https://doi.org/10.1016/S0966-6923(98)00027-1.

    Article  Google Scholar 

  55. Oses, U., Rojí, E., Cuadrado, J., & Larrauri, M. (2018). Multiple-criteria decision-making tool for local governments to evaluate the global and local sustainability of transportation systems in urban areas: Case study. Journal of Urban Planning and Development, 144(1), 1–17. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000406.

    Article  Google Scholar 

  56. Cascetta, E., & Cartenì, A. (2014). A quality-based approach to public transportation planning: Theory and a case study. International Journal of Sustainable Transportation, 8(1), 84–106. https://doi.org/10.1080/15568318.2012.758532.

    Article  Google Scholar 

  57. Gwilliam, K. M. (2002). Cities on the move: A World Bank urban transport strategy review. Washington: The World Bank.

    Google Scholar 

  58. Hadas, Y. (2013). Assessing public transport systems connectivity based on Google Transit data. Journal of Transport Geography, 33, 105–116. https://doi.org/10.1016/j.jtrangeo.2013.09.015.

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank the post-graduates urban research team of the year of 2013-2015 for cooperating field survey and also gratified to Prof. Soumendu Chatterjee (S.C sir), Presidency University for providing structural questionnaires of trip generation survey required for the study. The authors would also like to thanks Dr. Utpal Roy, the University of Calcutta for his constructive support. At last but not the least, thanks to anonymous reviewers and especially to the Editor for their constructive comments and support.

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Correspondence to Santanu Dinda.

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Dinda, S., Ghosh, S. & Das Chatterjee, N. An analysis of transport suitability, modal choice and trip pattern using accessibility and network approach: a study of Jamshedpur city, India. Spat. Inf. Res. 27, 169–186 (2019). https://doi.org/10.1007/s41324-018-0223-x

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