论文标题

量化流动性模式与码头无自行车用户的社会经济状况之间的关系

Quantifying relation between mobility patterns and socioeconomic status of dockless sharing-bike users

论文作者

Gao, Tianli, Xu, Zikun, Liu, Chenxin, Yang, Yu, Shang, Fan, Li, Ruiqi

论文摘要

自行车是一个最健康,最绿色,最负担得起的运输方式之一,但由于收集数据的限制,很少研究拥有收入不同的骑手的行动性模式。新兴的无码自行车共享平台记录有关每次旅行的详细信息,为我们提供了一个独特的机会。归因于其更好的使用灵活性和可访问性,在过去的几年中,无码头的自行车共享平台一直在蓬勃发展,并恢复了城市的骑行方式。在这项工作中,通过从码头共享平台中利用两种大型骑行记录,我们透露,包括收入不同的用户中的个别流动性模式,包括回旋半径和平均旅行距离,这表明人类都遵循类似的物理规则。但是,集体流动性模式,包括访问的平均范围和多样性以及通勤方向,所有收入类别均表现出不同的行为和空间模式。吸引更多自行车活动的热点位置在群体中截然不同,而用户居住的位置对于高收入和较低收入组的用户比率较低。较低的收入群体倾向于参观较少的繁荣地点,并通往两个城市的市中心的方向,并且在北京的出行多样性较小,但在上海的多样性较大。此外,在北京,社会经济类别之间流动性模式的差异比上海更明显。我们的发现将有助于为无码头的自行车共享平台设计更好的促销策略,并有助于过渡到更可持续的绿色运输。

Bikes are among the healthiest, greenest, and most affordable means of transportation for a better future city, but mobility patterns of riders with different income were rarely studied due to limitations on collecting data. Newly emergent dockless bike-sharing platforms that record detailed information regarding each trip provide us a unique opportunity. Attribute to its better usage flexibility and accessibility, dockless bike-sharing platforms are booming over the past a few years worldwide and reviving the riding fashion in cities. In this work, by exploiting massive riding records in two megacities from a dockless bike-sharing platform, we reveal that individual mobility patterns, including radius of gyration and average travel distance, are similar among users with different income, which indicates that human beings all follow similar physical rules. However, collective mobility patterns, including average range and diversity of visitation, and commuting directions, all exhibit different behaviors and spatial patterns across income categories. Hotspot locations that attract more cycling activities are quite different over groups, and locations where users reside are of a low user ratio for both higher and lower income groups. Lower income groups are inclined to visit less flourishing locations, and commute towards the direction to the city center in both cities, and of a smaller mobility diversity in Beijing but a larger diversity in Shanghai. In addition, differences on mobility patterns among socioeconomic categories are more evident in Beijing than in Shanghai. Our findings would be helpful on designing better promotion strategies for dockless bike-sharing platforms and towards the transition to a more sustainable green transportation.

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