基于人口迁徙大数据的城市对外交通客运方式优势出行距离研究

为提高我国城市对外交通中客运多方式协同运行效率，优化客运资源配置，依托人口迁徙大数据，建立量化分析城市对外交通客运方式优势出行距离的方法. 提出用绝对优势出行距离和相对优势出行距离来表征优势出行距离，分别构建城市对外客运方式的绝对优势出行距离模型和相对优势出行距离模型；利用人口迁徙大数据，绘制基于出行距离的客运方式分担率曲线，对优势出行距离模型进行求解. 结果表明，我国城市对外交通中公路、铁路、航空客运方式的绝对优势出行距离分别为8, 119] km、119, 1 594] km和1 594, 3 000] km，相对优势距离分别为8, 463] km、318, 983] km和2 477, 3 000] km.

Dominant Trip Distance of Urban External Passenger Transport Mode Based on Big Data of Migration

In order to improve the efficiency of multi-modal coordinated operation and optimize the resource allocation of passenger transport in China's urban external transport, this study proposed a method to quantitatively analyze the dominant trip distance of passenger traffic modes in urban external transport based on big data of population migration. Firstly, absolute dominant trip distance and relative dominant trip distance were proposed to define dominant trip distance. Then two types of the dominant trip distance model for urban external passenger transport mode were developed respectively. Finally, using the big data of population migration, the passenger transport mode share curve based on trip distance was drawn, and the dominant trip distance model was solved. The results show that in recent years, the absolute dominant trip distances of highway, railway and airway passenger transport modes are 8, 119] km、119, 1 594] km and 1 594, 3 000] km respectively, while the relative dominant trip distances are 8, 463] km、318, 983] km and 2 477, 3 000] km respectively.