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arXiv 1503.03021cs.SIcs.CYphysics.soc-ph
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OpenStreetCab:利用纽约市的出租车移动模式降低通勤成本

OpenStreetCab: Exploiting Taxi Mobility Patterns in New York City to Reduce Commuter Costs

Vsevolod Salnikov, Renaud Lambiotte, Anastasios Noulas, Cecilia Mascolo

摘要:

Uber作为全球替代出租车运营商的崛起最近吸引了很多人的兴趣。除了讨论这一新现象的媒体头条新闻,例如它如何破坏传统的交通运输业,政策制定者,经济学家,公民和科学家们还围绕如何将新一代共享经济服务整合到城市生态系统中进行了讨论。在这项工作中,我们的目标是通过利用一个公开的纵向数据集,描述了纽约市黄色出租车的流动性,揭示新的讨论。除了移动之外,该数据还包含出租车客户每次旅行所支付的费用的信息。因此,我们有机会在世界上最大的大都市之一提供标志性的黄色出租车与其现代竞争对手优步之间的首次面对面比较。我们确定了Uber出租车服务的最便宜版本Uber X在相同旅程中往往比黄色出租车更贵的情况。我们还展示了Uber的经济模式如何有效地利用了人类运动中众所周知的模式。最后,我们把我们的分析更进一步,提出了一个新的移动应用程序,比较出租车价格在城市,以方便旅客的出租车选择,希望最终导致通勤成本的降低。我们的研究提供了一个案例,说明公开的大型数据集如何通过为缺乏最新法规的经济部门提供透明度的机会来改善消费者的城市服务。

英文摘要:

The rise of Uber as the global alternative taxi operator has attracted a lot of interest recently. Aside from the media headlines which discuss the new phenomenon, e.g. on how it has disrupted the traditional transportation industry, policy makers, economists, citizens and scientists have engaged in a discussion that is centred around the means to integrate the new generation of the sharing economy services in urban ecosystems. In this work, we aim to shed new light on the discussion, by taking advantage of a publicly available longitudinal dataset that describes the mobility of yellow taxis in New York City. In addition to movement, this data contains information on the fares paid by the taxi customers for each trip. As a result we are given the opportunity to provide a first head to head comparison between the iconic yellow taxi and its modern competitor, Uber, in one of the world's largest metropolitan centres. We identify situations when Uber X, the cheapest version of the Uber taxi service, tends to be more expensive than yellow taxis for the same journey. We also demonstrate how Uber's economic model effectively takes advantage of well known patterns in human movement. Finally, we take our analysis a step further by proposing a new mobile application that compares taxi prices in the city to facilitate traveller's taxi choices, hoping to ultimately to lead to a reduction of commuter costs. Our study provides a case on how big datasets that become public can improve urban services for consumers by offering the opportunity for transparency in economic sectors that lack up to date regulations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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