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RAPID/Collaborative Research: Measuring the Impact of An Unanticipated Disruption of On-Demand Ride Services in Austin, Texas

RAPID/Collaborative Research: Measuring the Impact of An Unanticipated Disruption of On-Demand Ride Services in Austin, Texas
RAPID/协作研究:衡量德克萨斯州奥斯汀按需乘车服务意外中断的影响
批准号:
1647517
负责人:
Robert Hampshire
金额:
$2.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-01 至 2017-08-31

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中文摘要
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英文摘要
The recent indefinite suspension of crowdsource-based ridesharing services in Austin, Texas provides a unique and time-limited opportunity to observe the impact of these services on the public?s travel behavior. This project investigate how the disruption of ride sourcing services impacts residents? travel demand. It will document and analyze the adaptations that ride-sharing passengers make in response to the suspension of these services. Of particular attention are trips that utilize multiple travel modes, especially where these services provide the so-called first- and last-mile links to the public transit systems. The data and analyses produced through this work will thereby contribute information that could inform policy makers in other cities in which crowdsource-based transportation services are or may become active. Research findings are expected to benefit society by providing invaluable insights on on-demand mobility as it relates to both transportation and environmental policies. Using surveys administered online to users of these services, an assessment of the disruption on key measures of travel behavior will be made, including the number of trips, types of activities, travel mode choice, trip purpose and trip distribution. The survey, to be administered over a 6-8 week period, will utilize a systematic sampling methodology, allowing for broad participation among the population of former users. Efforts will be made to increase the response rate by utilizing social media to reach former users. Deliverables associated with the research include methodological tools and a unique dataset that will supporting modeling the resilience of multi-modal transportation systems.
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Convergence Accelerator Phase I(RAISE): Network for Equity in the Era of Driverless Vehicles
RAPID/Collaborative Research: Measuring the Impact of the Re-entry of Ride Sourcing in Austin, Texas: A Natural Experiment
CAREER: Smart Mobility Services: Operations and Policy
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