[1] Ren Gang, Zhou Zhuping, Zhang Haoran,. Application of discrete choice modelin trip mode structure forecast: a case study of Bengbu [J]. Journal of Southeast University (English Edition), 2011, 27 (1): 83-87. [doi:10.3969/j.issn.1003-7985.2011.01.017]

Copy

Application of discrete choice modelin trip mode structure forecast: a case study of Bengbu()

Share：

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

27

Issue:

2011 1

Page:

83-87

Research Field:

Traffic and Transportation Engineering

Publishing date:

2011-03-30

Info

Title:

Application of discrete choice modelin trip mode structure forecast: a case study of Bengbu

Author(s):

Ren Gang¹;  Zhou Zhuping¹;  Zhang Haoran²

¹ School of Transportation, Southeast University, Nanjing 210096, China
² Zhuhai Transport Bureau, Zhuhai 519001, China

Keywords:

trip mode split;  trip mode structure;  discrete choice model;  forecasting

PACS:

U491.1

DOI:

10.3969/j.issn.1003-7985.2011.01.017

Abstract:

In order to find the main factors that influence the urban traffic structure, a relational model between the travelers’ characteristics and the trip mode choice is built. The data of urban residents’ characteristics are obtained from statistical data, while the trip mode split data is collected through a trip survey in Bengbu. In addition, the discrete choice model is adopted to build the functional relationship between the mode choice and the travelers’ personal characteristics, as well as family characteristics and trip characteristics. The model shows that the relationship between the mode split and the personal, as well as family and trip characteristics is stable and changes little as the time changes. Deduced by the discrete model, the mode split result is relatively accurate and can be feasibly used for trip mode structure forecasts. Furthermore, the proposed model can also contribute to find the key influencing factors on trip mode choice, and restructure or optimize the urban trip mode structure.

References:

[1] McFadden D. Conditional logit analysis of qualitative choice behavior [J]. Frontiers in Econometrics, 1974, 1(2): 105-142.
[2] Ben-Akiva M, Lerman S R. Discrete choice analysis: theory and application to travel demand [M]. Cambridge, MA, USA: The MIT Press, 1985.
[3] Koppelman F S, Sethi V. Incorporating variance and covariance heterogeneity in the generalized nested logit model: an application to modeling long distance travel choice behavior [J]. Transportation Research Part B, 2005, 39(9): 825-853.
[4] Guan Hongzhi. Disaggregate model: a tool of traffic behavior analysis [M]. Beijing: China Communications Press, 2004.(in Chinese)
[5] Liu Zhen, Zhou Xizhao. Application on nested logit mode of trip mode choice [J]. Journal of Shanghai Maritime University, 2006, 27(3):66-70.(in Chinese)
[6] Jin An. On methodology of parameter estimation in logit model [J]. Journal of Transportation Systems Engineering and Information Technology, 2004, 4(1):71-75.
[7] Zhou Jian, Wang Shusheng, Sui Shuixian. Study on nested logit model for transport mode split and its solution[J]. Journal of Shandong Jiaotong Universiy, 2005, 13(4): 28-31.(in Chinese)
[8] Luo Qingyu, Sun Baofeng, Wu Wenjing, et al. Predicting traffic mode split under congestion pricing based on mixed logit model [J]. Journal of Jilin University: Engineering and Technology Edition, 2010, 40(5): 1230-1234.(in Chinese)
[9] Bliemer M C J, Rose J M, Hensher D A. Efficient stated choice experiments for estimating nested logit models [J]. Transportation Research Part B, 2009, 43(1): 19-35.
[10] Rouwendal J, de Blaeij A, Rietveld P, et al. The information content of a stated choice experiment: a new method and its application to the value of a statistical life [J]. Transportation Research Part B, 2010, 44(1): 136-151.
[11] 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 [J]. Transportation Research Part A, 2007, 41(5): 428-443.
[12] Hensher D A. Empirical approaches to combining revealed and stated preference data: some recent developments with reference to urban mode choice [J]. Research in Transportation Economics, 2009, 23(1): 23-29.
[13] Shao Chunfu. Traffic planning [M]. Beijing: China Railway Publishing House, 2006.(in Chinese)
[14] Jiao Pengpeng, Lu Huapu, Yang Lang. Disaggregate traffic mode choice model based on combination of revealed and stated preference data [J]. Tsinghua Science and Technology, 2006, 11(3): 351-356.(in Chinese)
[15] Train K E. Discrete choice methods with simulation [M]. Cambridge: Cambridge University Press, 2003.

Memo

Memo:

Biography: Ren Gang(1976—), male, doctor, researcher, rengang@seu.edu.cn.
Foundation item: The National Natural Science Foundation of China(No. 50738001, 51078086).
Citation: Ren Gang, Zhou Zhuping, Zhang Haoran. Application of discrete choice model in trip mode structure forecast: a case study of Bengbu[J].Journal of Southeast University(English Edition), 2011, 27(1):83-87.[doi:10.3969/j.issn.1003-7985.2011.01.017]

Common functions