关键词: 城市交通, 缺失模式, 期望最大化修补方法, 出行方式选择, 多项Logit集计模型, 发展中城市, 出行时间价值

Abstract: To enhance the quality of transportation planning and policy making, it is necessary to properly deal with the nonresponse issues in transport surveys. However, such nonresponse issues especially in developing countries have been ignored in literature. This paper first statistically identifies the missing patterns of item nonresponse (INR) in person trip survey data collected in developing cities and then analyzes the effects of INR on the performance of travel mode choice model (an aggregated multinomial logit model) based on expectation-maximization (EM) imputation method. As a case study, three developing cities representing three levels of INR are analyzed as follow. Firstly, the statistically significant social-economic attributes of trip makers and trip-context factors are identified with respect to INR in the missing pattern analysis by using Chi-Square test method. Secondly, EM imputation based on missing pattern analysis is applied to deal with missing data to obtain the unbiased data set as a benchmark. Thirdly, the null hypothesis that the model parameters estimated with and without imputation are equal is statistically tested using independent-sample T tests and further the internal validity performed in terms of R-squared coefficients is used to identify the discrepancy of model predictions between with and without imputations. Finally, one critical indicator-value of travel time (VOTT) is evaluated considering the effects of missing data. The results confirm that the respondents and non-respondents are quite different in terms of the social-economic background in the developing cities and further show that not only the missing rates but also the missing patterns greatly affect the performance of mode choice model in terms of model parameters and the prediction ability. The calculation of VOTT reveals that the VOTT affected by INR tends to be overestimated.

Key words: urban traffic, missing pattern, EM imputation, travel mode choice, aggregated multinomial logit model, developing cities, value of travel time