场景导向的定制公交出行需求宏微观数据嵌套分析

A Scenario-Oriented Macro and Micro Data Nested Analysis Method for Customized Bus Travel Demand

潜在出行需求分析是定制公交市场推广的基础,然而现有相关研究多关注特定出行场景下的宏观需求特征或方式选择意愿,难以整体把握定制公交的各种适用场景与对应的潜在出行需求特点。结合大数据特征挖掘和小样本个体行为调查的各自优势,提出了一种场景导向的定制公交潜在出行需求宏微观数据嵌套分析方法:利用出行大数据挖掘出行需求的宏观特征,基于小样本调查数据提取微观个体的方式选择意愿,通过一致的出行场景实现上述两方面结论的嵌套连接,进而研判各场景下的定制公交潜在出行需求。以厦门市为例验证方法的可操作性及数据适用性。结果表明,可依据潜在出行需求特点将各种出行场景划分为“高需求量、高转移率”等4类,进而对应制定差异化的定制公交市场推广策略。

Analyzing the potential travel demand for customized buses is the basis of the service promotion.However,the existing relevant research focuses on the macro demand characteristics or mode choices’willingness under specific travel scenarios,which is difficult to generalize the various application scenarios and corresponding potential demand characteristics of customized bus systems.Combining the respective advantages of large data feature mining and small sample individual behavior,this paper puts forward a scenario-oriented macro and micro nested analysis method for customized bus travel demand.To estimate the customized bus travel demand in different scenarios,big data mining is utilized to reveal the macro characteristics of travel demand,and a small sample survey can help obtain the mode choices’willingness of micro individuals and analyze the nested connection through consistent travel scenarios.Then,Xiamen is selected as an example to verify the applicability of the method.The results show that,according to the characteristics of potential demand,various travel scenarios can be divided into four types including“high demand,high mode-shift rate”,corresponding to differentiated customized public transportation marketing strategies.