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根据以往我国城市绿色交通的调查结论,设计调查问卷,调查之后进行分析。运用Logit回归模型,建立一个专门针对二元因变量的Binary Logit模型,得出以下结论:收入水平、交通拥堵状况、对小汽车的态度和低碳环保意识4个变量因为统计检验不显著而未能进入最终模型。同时,油价、停车费、居所附近的直达公交线路、居所附近的轨道交通、公共交通乘坐舒适度、工作日平均出行距离与居民绿色出行方式的选择具有显著相关关系。
According to the survey results of urban green traffic in the past, the questionnaire was designed and analyzed after the investigation. Using the Logit regression model to establish a Binary Logit model that is specific to the binary dependent variable, we draw the following conclusions: income level, traffic congestion, car attitudes and environmental awareness of low carbon 4 variables because the statistical test is not significant and not Can enter the final model. At the same time, oil prices, parking fees, direct bus lines around the residence, rail transit near the residence, riding comfort of public transport, and average travel distance of working days were significantly related to the choice of residents’ green travel modes.