NL Model on Traffic Mode Split among High-Density Town Cluster

Abstract:

With urbanization process acceleration in China, traffic travel among cities becomes increasing, and traffic mode split is the key link of traffic passenger flow forecast among cities. In this paper, the concept of high-density town cluster was proposed to analyze the characteristics of development, population composition, and traffic facilities among high-density town cluster. Based on applicability analysis of aggregate model and disaggregate model, survey content of revealed preference (RP) and stared preference (SP), and traffic mode hierarchical division according to average speed, then NL disaggregate model among high-density town cluster was constructed. NL model which was parameter calibrated and validated with DongGuan citizen travel investigation data in 2009 was used to analyze the trend of traffic mode split. The result shows that high-density town cluster, such as DongGuan, are establishing a three-dimensional travel mode set, including high-speed rail, intercity rail, suburban rail, urban rail transit, intercity express bus, car, taxi, and common public transport. With the network of multi-mode rail transit further improving, ratio on choosing the traffic mode of multi-mode rail transit, such as high-speed rail, intercity rail, suburban rail, urban rail transit, increases dramatically.

• Periodical: Advanced Engineering Forum (Volume 5)
• Pages: 99-104
• DOI: https://doi.org/10.4028/www.scientific.net/AEF.5.99
• Online since: July 2012
• Authors: Shi Mei Wu, Yu Long Pei
• Keywords: High-Density Town Cluster, Multi-Mode Rail Transit, NL Model, Traffic Travel Mode, Transportation Planning

References

[1] X. J. Li. Town high-density area and town cluster planning-practices and understanding. Journal of Urban Planning, (2008) 1-7.

[2] H. P. Lu. Theory and method in transportation planning. Tsing Hua University Press. 1998, pp.56-73.

[3] Kenneth E Train. Discrete choice methods with simulation. Cambridge University Press, 2003, pp.45-62.

[4] H. Z. Guan. Disaggregate Model-Traffic Behavior Analysis Tools. China Communications Press, 2004, pp.27-42.

[5] H. R. Zhu. Study on traffic behavior characteristics and traffic mode choice based on activity analysis. Tongji University, (2005) 32-36.

[6] Hensher D, Greene W. Specification and estimation of the nested logit model: Alternative Normalizations. Transportation Research B, 36 (2002) 3-15.

DOI: 10.1016/s0191-2615(00)00035-7

[7] H. R. Zhang, G. Ren, W. Wang. Application of discrete choice model in trip mode structure forecasting. Journal of Transportation Systems Engineering and Information Technology, 5 (2008) 44-49.

[8] A. Jin. On methodology of parameter estimation in logit model. Journal of Transportation Systems Engineering and Information Technology, 4 (2004) 71-75.

[9] W. T. Zhang. SPSS 11 Statistical Analysis Course. Beijing, 2002.