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A spatial econometric model for travel flow analysis and real-world applications with massive mobile phone data

机译:具有大量手机数据的旅行流分析和实际应用的空间计量经济学模型

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摘要

Cellular signaling data provide a massive and emerging source for acquiring urban origin destination (OD) travel flow information, supporting decision making on large-scale mobility enhancement, and enabling the exploration of factors that influence travel demand. This study investigates the effects of population, facilities, and transit accessibility on travel flows between traffic analysis zones. A spatial econometric model is employed for the OD travel flow analysis by integrating massive mobile data with other explanatory features of urban regions. The results of real-world applications in Hangzhou, China, show that: (I) all coefficients of the origin dependence, destination dependence, and OD dependence are statistically significant, which verifies the consideration of the spatial interdependence in the OD flow modeling; (II) all of the permanent population, number of facilities, and transit accessibility have positive correlations with travel flows; and (III) travel time, as expected, is negatively correlated with the travel flow volume. Finally, policy implications are discussed, further contributing to the design of urban land use and transportation policies.
机译:蜂窝信令数据为获取城市出发地(OD)的旅行流程信息提供了一个庞大且新兴的来源,支持进行大规模移动性增强的决策,并能够探索影响旅行需求的因素。这项研究调查了人口,设施和交通可达性对交通分析区域之间旅行流量的影响。通过将大量的移动数据与城市地区的其他说明性特征相结合,将空间计量经济学模型用于OD旅行流量分析。在中国杭州的实际应用结果表明:(I)起点依赖,目的地依赖和OD依赖的所有系数在统计上都是显着的,这验证了OD流量建模中空间相互依赖的考虑; (II)所有常住人口,设施数量和交通便利性与出行流量呈正相关; (III)如预期的那样,行进时间与行进流量负相关。最后,讨论了政策含义,进一步有助于设计城市土地使用和运输政策。

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