基于分层logit模型的旅游交通方式选择研究

通过对旅客进行旅游交通方式选择的量化研究,得出各交通方式的选择概率,有利于各旅游地进行规划。首先通过分析过去与现在人们旅游交通工具的选择的不同,得出影响交通工具选择的影响因素。然后根据各个影响因素建立分层logit预测模型,对水平1和水平2进行标定,得出各个影响因素的参数值,从而得到各交通方式的选择概率。再利用该建模对近、中、远3种距离模式进行交通工具选择的预测,最后得到的预测结果与实际情况较为符合,相差的概率在0.05以内。

A Nested Logit Model of Tourist Traffic Mode Choice

To improve tourism areasr transportation planning, this paper quantitatively analyzes tourist traffic mode choice and generates the selection probability of each mode. The factors that influence the traveling traffic mode choice are found by comparing people＇s past and present choices of traffic mode, and a nested logit model is built to compute the val- ue of each factor by calibrating Level 1 and Level 2. Selection probabilities of traffic modes are generated and used to predict traffic mode choices in short, middle, and long distance. The results show that the predicted values are very close to the real-life situations （the differences between predicted values and actual values are all within 0.05）.