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Modeling Americans' autonomous vehicle preferences: A focus on dynamic ride-sharing, privacy & long-distance mode choices

机译:建模美国人的自主车偏好:专注于动态乘车共享,隐私与长途模式选择

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Rapid advances in technologies have accelerated the timeline for public use of fully-automated and communications-connected vehicles. Public opinion on self-driving vehicles or AVs is evolving rapidly, and many behavioral questions have not yet been addressed. This study emphasizes AV mode choices, including Americans' willingness to pay (WTP) to ride with a stranger in a shared AV fleet vehicle on various trip types and the long-distance travel impacts of AVs. Exactly 2,588 complete responses to a stated-preference survey with 70 questions provide valuable insights on privacy concerns, safety and dynamic ride-sharing with strangers, long-distance travel and preferences for smarter vehicles and transport systems. Two hurdle models (which allow for a high share of zero-value responses) were estimated: one to predict WTP to share a ride and another to determine WTP to anonymize location while using AVs, and a multinomial logit was developed to estimate long-distance mode choices with AVs and SAVs available. Results suggest that WTP to share rides will rise over time, for a variety of reasons, and SAV use will be particularly popular for long-distance business travel. Elasticity estimates suggest that privacy may not be an important concern for AV-based travel.
机译:技术的快速进步加速了公共使用全自动和通信连接的车辆的时间表。对自动驾驶车辆或AVS的公众舆论正在快速发展,许多行为问题尚未解决。本研究强调了AV模式选择,包括美国人支付(WTP)的意愿,在各种旅行类型和AVS的长途旅行冲击中骑在共用AV车队车辆中的陌生人。恰好2,588对具有70个问题的规定优先调查的完全答案提供了对隐私问题,安全性和动态乘车与陌生人,长途旅行和偏好的智能车辆和运输系统的偏好提供有价值的见解。估计两个障碍模型(允许高零值响应):一个用于预测WTP以共享乘坐,另一个用于使用AVS的匿名位置确定WTP,并且开发了多项式Lo​​git以估计远程距离使用AVS和SEL可用模式选择。结果表明,由于各种原因,WTP分享游乐设施将随着时间的推移而上升,并且Sav使用将特别适合长途商务旅行。弹性估计表明隐私可能不是基于AV的旅行的重要关注。

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