Public Transportation Share Ratio Prediction Based on Disaggregate Dogit Model


Article Preview

In order to analyze the distributing condition of urban passenger flow scientifically and correctly, the disaggregate Dogit model is presented to predict the public transportation share ration in city, which is carried out by means of analysis of the outer and inner factors that affect the choice of modes of transportation and is based on the random utility theory. Establishment of the model, parameter identification and the process of calculation are described in detail. Finally, according to the proposed algorithm, the public transportation share ratio forecast test is carried out using the field survey data. The results of independent sample test indicate that the model has a finer precision and stability.



Advanced Materials Research (Volumes 378-379)

Edited by:

Brendan Gan, Yu Gan and Y. Yu




B. Y. Qi and H. L. Dou, "Public Transportation Share Ratio Prediction Based on Disaggregate Dogit Model", Advanced Materials Research, Vols. 378-379, pp. 191-195, 2012

Online since:

October 2011





[1] NIU Xueqin, WANG Wei, YIN Zhiwei. Research on method of urban passenger traffic mode split forecast [J]. Journal of highway and transportation research and development, 2004, 21(3): 75-78.

[2] WANG Zheng, LIU An, ZHENG Ping. Generalized logit method for traffic modal splitting [J]. Journal of Tongji University, 1999, 27(3) :314-318.

[3] LIU Zhiming, DENG Wei, GUO Tangyi. Application of disaggregate model based on RP/SP survey to transportation planning [J]. Journal of transportation engineering and information, 2008, 6(3): 59-64.

[4] Ahmed Hamdy Ghareib. Evaluation of logit and probit models in mode-choice situation [J]. Journal of transportation engineering, 1996, 122(4): 282-290.


[5] LIU Canqi. Advanced traffic planning [M]. Beijing: China communications press, (2001).

[6] Math department of Fudan University. Probability and mathematical statistics [M]. Beijing: People's education press, (1979).

[7] WANG Jichuan, Guo Zhigang. Logisitic regression models, method and application [M]. Beijing: Higher education press, 2001, 9.

[8] YU Xiulin, REN Xuesong. Multivariable statistics analysis [M]. Beijing: China statistics press, (1999).

[9] HU Hua, TENG Jing, GAO Yunfeng et al. Research on travel mode choice behavior under integrated multi-modal transit information service [J]. China Journal of Highway and Transport, 2009, 22(2): 87-92.


Fetching data from Crossref.
This may take some time to load.