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Modelling and Analysis of Mode Choice Behaviour for Work Trips in Srinagar

  • Suhail Ahmad KhandayEmail author
  • Mokaddes Ali Ahmed
Conference paper
  • 77 Downloads
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 12)

Abstract

Mode choice of work trip makers residing in Srinagar during summer were estimated by using a multinomial logit model with statistical data processing software SPSS. 638 work trip maker samples were collected, of which 21 samples were rejected and finally 617 samples were used for model estimation. Several attributes such as travel cost, riding time, waiting time, vehicle ownership, travel distance and age are found to be significant for mode choice behavior of work trips. The model was calibrated using two third data sets and for validation test one- third of the data sets were used. The findings of the research will aid private transport providers, government and public transportation organizations in evading over/under-designing of demanded services and amenities and the making of acceptable choices. Prediction of the future intercity transport requirement and evaluation of present public transport in Srinagar can be estimated from the outcomes of this study.

Keywords

Mode Attributes Trip makers Multinomial logit model Srinagar Utility 

References

  1. 1.
    Waddell, P., Ulfarsson, G.F., Franklin, J.P., Lobb, J.: Incorporating land use in metropolitan transportation planning. Transp. Res. Part A Policy Pract. 41(5), 382–410 (2007)CrossRefGoogle Scholar
  2. 2.
    Pel, A.J., Bliemer, M.C.J., Hoogendoorn, S.P.: A review on travel behaviour modelling in dynamic traffic simulation models for evacuations. Transportation 39(1), 97–123 (2012)CrossRefGoogle Scholar
  3. 3.
    de Dios Ortúzar, J., Willumsen, L.G.: Modelling Transport. Wiley, Chichester (2011)CrossRefGoogle Scholar
  4. 4.
    Ben-Akiva, M.E., Lerman, S.R.: Discrete Choice Analysis: Theory and Application to Travel Demand, vol. 9. MIT Press, Cambridge (1985)Google Scholar
  5. 5.
    Le Loo, L.Y., Corcoran, J., Mateo-Babiano, D., Zahnow, R.: Transport mode choice in South East Asia: Investigating the relationship between transport users’ perception and travel behaviour in Johor Bahru, Malaysia. J. Transp. Geogr. 46, 99–111 (2015)CrossRefGoogle Scholar
  6. 6.
    Ben-Akiva, M., Bierlaire, M.: Discrete choice methods and their applications to short term travel decisions. In: Hall, R.W. (ed.) Handbook of Transportation Science, pp. 5–33. Springer, Boston (1999)CrossRefGoogle Scholar
  7. 7.
    De Palma, A., Rochat, D.: Mode choices for trips to work in Geneva: an empirical analysis. J. Transp. Geogr. 8(1), 43–51 (2000)CrossRefGoogle Scholar
  8. 8.
    Rasouli, S., Timmermans, H.: Activity-based models of travel demand: promises, progress and prospects. Int. J. Urban Sci. 18(1), 31–60 (2014)CrossRefGoogle Scholar
  9. 9.
    Verplanken, B., Aarts, H., Van Knippenberg, A.: Habit, information acquisition, and the process of making travel mode choices. Eur. J. Soc. Psychol. 27(5), 539–560 (1997)CrossRefGoogle Scholar
  10. 10.
    Bhatta, B.P., Larsen, O.I.: Errors in variables in multinomial choice modeling: a simulation study applied to a multinomial logit model of travel mode choice. Transp. Policy 18(2), 326–335 (2011)CrossRefGoogle Scholar
  11. 11.
    Dieleman, F.M., Dijst, M., Burghouwt, G.: Urban form and travel behaviour: micro-level household attributes and residential context. Urban Stud. 39(3), 507–527 (2002)CrossRefGoogle Scholar
  12. 12.
    Kuchay, N.A., Bhat, M.S.: Analysis and simulation of urban expansion of Srinagar city. Transactions 36(1), 109–121 (2014)Google Scholar
  13. 13.
    Albert, A., Anderson, J.A.: On the existence of maximum likelihood estimates in logistic regression models. Biometrika 71(1), 1–10 (1984)MathSciNetCrossRefGoogle Scholar
  14. 14.
    So, Y., Kuhfeld, W.F.: Multinomial logit models. In: SUGI 20 Conference Proceedings, pp. 1227–1234 (1995)Google Scholar
  15. 15.
    Tushara, T., Rajalakshmi, P., Bino, I.K.: Mode choice modelling for work trips in Calicut City. Int. J. Innov. Technol. Explor. Eng. (2013). ISSN 2278–3075Google Scholar
  16. 16.
    Blandon, J., Henson, S., Islam, T.: Marketing preferences of small-scale farmers in the context of new agrifood systems: a stated choice model. Agribus. Int. J. 25(2), 251–267 (2009)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Civil EngineeringNational Institute of Technology, SilcharSilcharIndia

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