Development of mode choice models of a trip maker for Hyderabad metropolitan city

  • Authors

    • Bollini Prasad 1Assistant Professor, Department of Civil Engineering, CMR College of Engineering & Technology,Kandlakoya, Hyderabad, Telangana, India - 501401.
    • Kumar Molugaram Professor of Civil Engineering, Department of Civil Engineering, College of Engineering, Osmania University, Hyderabad, India.
    2018-01-28
    https://doi.org/10.14419/ijet.v7i1.6.9014
  • Mode Choice Modeling, Binary Logit Models, Multinomial Logit Models, Trip Maker, And Travel Demand Modeling.

  • Abstract

    The rapid development of urbanization, population growth and the rapid development of economy resulted in the rapid increase in the total number of motor vehicles in the modern cities of India. Consequently, the importance of forecasting of the travel demand model has been increased in the recent years. Forecasting of the travel demand model involves various stages of trip generation and distribution, mode choice and traffic assignment. Among these stages, the mode choice analysis is a prominent stage as it considers the travelers mode to reach their destination. Further, study of mode choice criteria has become a vital area of research as individual and household socio-demographics exert a strong influence on travel mode choice decisions. There is a huge literature on travel model choice modeling to predict the range of trade-offs of transportation of commuters considering travel time and travel cost. In such literature intercity mode choice behavior has gained significant attention by several authors. In this study an attempt has made in order to calculate the model share of the different modes between the circle to the circle, and it is found that the modal share of 2-wheeler is 70 %, bus is about 23 % and car is about 7% of the total trips.

  • References

    1. [1] Ashiabor, S., H. Baik and A. Trani, 2007. Logit Models to Forecast Nationwide Intercity Travel Demand in the United States. Transportation Research Record: Journal of the Transportation Research Board, No. 2007, Transportation Research Board of the National Academies, Washington, D.C., pp: 1-12.

      [2] Forinash, C.V. and F.S. Koppelman, 1993. Application and interpretation of nested logit models of intercity mode choice. Transport. Res. Record, 1413: 98-106.

      [3] Grayson, A., 1981. Disaggregate model of choice in intercity travel. Transport. Res. Record, 835: 36-42.

      [4] Mandel, G. and Rothengatter, 1997. A disaggregate box-cox logit mode choice model of intercity passenger travel in Germany and its implications for high-speed rail demand forecasts. Ann. Region. Sci., 31: 99-120.

      [5] Praveen, K.M. and C. Mallikarjuna, 2011. Mode choice modelling for intercity transportation in India: A case of Guwahati to five metro cities. Int. J. Earth Sci. Eng., 04(06): 364-374.

      [6] Wilson, R.F., S. Damodaran and J.D. Innes, 1990. Disaggregate mode choice models for intercity passenger travel in Canada. Canadian J. Civil Eng., 17: 184-191.

      [7] Cornelia Richter, Stephan Keuchel, 2012, Modelling Mode Choice in Passenger Transport with Integrated Hierarchical Information. Journal of Choice Modeling, 5(1), 2012, pp1-21

      [8] Madhu, D. 2008. Fuzzy Logic Based Micro-Scopic Traffic Simulation Model for Transport Policy Evaluation. Gifu University, Japan: PhD Thesis.

      [9] Omer Khan, 2007. Modelling Passenger Mode Choice Behavior Using computer Aided Stated Preference Data, School of Urban Development, Queensland University of Technology, Queensland: PhD Thesis.

      [10] Xiao-Shan Lu, Hai-Jun Huang*, Tian-Liang Liu. Pricing and hierarchical logit-based mode choice models in a multimodal corridor with trip-chain costs. Beijing University of Aeronautics & Astronautics, Beijing 100191, China. Systems Engineering Procedia 2 (2011) 231 – 242https://doi.org/10.1016/j.sepro.2011.10.031.

      [11] Horowitz. J. L (1991) Reconsidering the Multinomial Probit Model. Transportation Research part B: Methodological, 26(6), PP 433-438.https://doi.org/10.1016/0191-2615(91)90036-I.

      [12] Zhihu Zhang, Hongzhi Guan, Huanmei Qin and YungiangXue (2013) A Traffic Mode Choice Model for the Bus user Groups Based on SP and Rp Data. 13th COTA International conference of Transportation Professionals (CICTP 2013), Elsevier 96(2013), PP 382-389.https://doi.org/10.1016/j.sbspro.2013.08.045.

      [13] Yaowuwang, chuan ding, chaoliu,bingleixie (2013) an analysis of international freight mode choice between truck and rail : a case study of mary land , united states.13th COTA International conference of Transportation Professionals (CICTP 2013), Elsevier 96(2013), PP 1239-1249.

      [14] Winston c. (1983). The demand for freight transportation: models and applications. Transportation Research part A, volume 17, no .6, PP 419-427.https://doi.org/10.1016/0191-2607(83)90162-0.

      [15] Shen.g and wang.j (2012). A freight mode choice analysis using a binary logit mode and gis: the case of creal grains transportation in the united states. Journal of Transportation Technologies, 2, PP 175-188.https://doi.org/10.4236/jtts.2012.22019.

      [16] Samimi, A. Kawamura,K, and Mohhammadian, A. (2011). A disaggregate analysis of rail-truck mode choice behaviors for freight shipments. The 90th Transportation Research Board Annual Meeting, CD-ROM, Washing ton D.C.

      [17] Philippe Gerber, HichemOmrani, Omar choarit, Anjali Awasthi. (2012). Predection of individual travel mode using evidential neural network model PP 1-17.

      [18] JianchuanXiamyu (2013) An exploration of the interdependencies between trip changing behavior and travel mode choice 13th COTA International conference of Transportation Professionals (CICTP 2013), Elsevier 96(2013), pp. 1967-1975.

      [19] Chandra R. Bhat, Alessamdroportoghese, Erika Spissu, Naveen Eluru, ItaloMeloni (2010), A Copula-Based joint model of commute mode choice and number of Non-work trips during the commute. PP 1-15.

      [20] Manssour A. Abdulsalam Bin Miskeen, Ahmed Mohamed Alhodairi, Rizaatiq Abdullah Bino and Rahmat. K (2013). Modeling a Multinomial logit Model of Intercity Travel Mode Choice Behavior for all trips in Libiya, International Journal of Civil Science and Engineering Vol: 7, No: 9 PP 132-141.

      [21] Mukesh Kumar, PradipSarkar, ErrampalliMadhu (2013). Development of Fuzzy Logic Based Mode Choice Model Considering Public transport policy options, International Journal for traffic and Transportation Engineering, 3(4): PP 408-425.

      [22] L. A. Zadeh, (1965) “Fuzzy sets†Information and control volume 8, No.3, PP 338-353.https://doi.org/10.1016/S0019-9958(65)90241-X.

      [23] ArunotayanunKriankrai, Johnw.Polak (2011), Taste Heterogencity and market segmentation in freight shippers’ mode choice behavior, Transportation research part E: Logistics and transportation review, Elsevier, volume 47, Issue 2, PP 138-148.

  • Downloads

  • How to Cite

    Prasad, B., & Molugaram, K. (2018). Development of mode choice models of a trip maker for Hyderabad metropolitan city. International Journal of Engineering & Technology, 7(1.6), 1-7. https://doi.org/10.14419/ijet.v7i1.6.9014

    Received date: 2018-01-03

    Accepted date: 2018-01-17

    Published date: 2018-01-28