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The impact of ride-hailing on vehicle miles traveled

机译:乘车对行驶里程的影响

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Ride-haling such as Uber and Lyft are changing the ways people travel. Despite widespread claims that these services help reduce driving, there is little research on this topic. This research paper uses a quasi-natural experiment in the Denver, Colorado, region to analyze basic impacts of ride-hailing on transportation efficiency in terms of deadheading, vehicle occupancy, mode replacement, and vehicle miles traveled (VMT). Realizing the difficulty in obtaining data directly from Uber and Lyft, we designed a quasi-natural experiment-by one of the authors driving for both companies-to collect primary data. This experiment uses an ethnographic and survey-based approach that allows the authors to gain access to exclusive data and real-time passenger feedback. The dataset includes actual travel attributes from 416 ride-hailing rides-Lyft, UberX, LyftLine, and UberPool-and travel behavior and socio-demographics from 311 passenger surveys. For this study, the conservative (lower end) percentage of deadheading miles from ride-hailing is 40.8%. The average vehicle occupancy is 1.4 passengers per ride, while the distance weighted vehicle occupancy is 1.3 without accounting for deadheading and 0.8 when accounting deadheading. When accounting for mode replacement and issues such as driver deadheading, we estimate that ride-hailing leads to approximately 83.5% more VMT than would have been driven had ride-hailing not existed. Although our data collection focused on the Denver region, these results provide insight into the impacts of ride-hailing.
机译:Uber和Lyft等骑行正在改变人们的出行方式。尽管人们普遍认为这些服务有助于减少驾驶,但是对此主题的研究很少。本研究论文在科罗拉多州丹佛市进行了一次准自然实验,从无人驾驶,乘员,模式更换和行驶里程(VMT)的角度分析了乘车对运输效率的基本影响。意识到直接从Uber和Lyft获得数据的困难,我们设计了一个准自然实验(由两家公司的两位作者共同推动)来收集原始数据。该实验使用人种学和基于调查的方法,使作者能够访问专有数据和实时乘客反馈。该数据集包括来自416个叫车服务的实际旅行属性-Lyft,UberX,LyftLine和UberPool,以及来自311个乘客调查的旅行行为和社会人口统计学。在本研究中,从打车起航的无头飞行里程的保守(低端)百分比为40.8%。每次乘车的平均载客量为1.4名乘客,而距离加权载客量为1.3(不计入空头)和0.8(计入空头)。考虑到模式更换和驾驶员无头驾驶等问题后,我们估计,如果不存在叫车服务,拼车服务将比驾驶汽车多出83.5%的VMT。尽管我们的数据收集集中在丹佛地区,但这些结果提供了对乘车影响的深刻见解。

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