Disaggregate Traffic Mode Choice Model Based on Combination of Revealed and Stated Preference Data  

作　　者：焦朋朋 陆化普 杨朗 

机构地区：[1]Institute of Transportation Engineering, Tsinghua University, Beijing 100084,China

出　　处：《Tsinghua Science and Technology》2006年第3期351-356,共6页清华大学学报（自然科学版（英文版）

基　　金：SupportedbytheNationalNaturalScienceFoundationofChina(No.50178042)

摘　　要：The conventional traffic demand forecasting methods based on revealed preference （RP） data are not able to predict the modal split. Passengers＇ stated intentions are indispensable for modal split forecasting and evaluation of new traffic modes. This paper analyzed the biases and errors included in stated preference data, put forward the new stochastic utility functions, and proposed an unbiased disaggregate model and its approximate model based on the combination of RP and stated preference （SP） data, with analysis of the parameter estimation algorithm. The model was also used to forecast rail transit passenger volumes to the Beijing Capital International Airport and the shift ratios from current traffic modes to rail transit. Experimental results show that the model can greatly increase forecasting accuracy of the modal split ratio of current traffic modes and can accurately forecast the shift ratios from current modes to the new mode.The conventional traffic demand forecasting methods based on revealed preference （RP） data are not able to predict the modal split. Passengers＇ stated intentions are indispensable for modal split forecasting and evaluation of new traffic modes. This paper analyzed the biases and errors included in stated preference data, put forward the new stochastic utility functions, and proposed an unbiased disaggregate model and its approximate model based on the combination of RP and stated preference （SP） data, with analysis of the parameter estimation algorithm. The model was also used to forecast rail transit passenger volumes to the Beijing Capital International Airport and the shift ratios from current traffic modes to rail transit. Experimental results show that the model can greatly increase forecasting accuracy of the modal split ratio of current traffic modes and can accurately forecast the shift ratios from current modes to the new mode.

关 键 词：disaggregate model stated preference data revealed preference data modal split shift ratio 

分 类 号：U116[交通运输工程]