The effect of ride experience on changing opinions toward autonomous vehicle safety

IF 12.5 Q1 TRANSPORTATION
Xiaowei Shi , Zhen Wang , Xiaopeng Li , Mingyang Pei
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引用次数: 46

Abstract

Autonomous vehicles (AVs) are a promising emerging technology that is likely to be widely deployed in the near future. People's perception on AV safety is critical to the pace and success of deploying the AV technology. Existing studies found that people's perceptions on emerging technologies might change as additional information was provided. To investigate this phenomenon in the AV technology context, this paper conducted real-world AV experiments and collected factors that may associate with people's initial opinions without any AV riding experience and opinion change after a successful AV ride. A number of ordered probit and binary probit models considering data heterogeneity were employed to estimate the impact of these factors on people's initial opinions and opinion change. The study found that people's initial opinions toward AV safety are significantly associated with people's age, personal income, monthly fuel cost, education experience, and previous AV experience. Further, the factors dominating people's opinion change after a successful AV ride include people's age, personal income, monthly fuel cost, daily commute time, driving alone indicator, willingness to pay for AV technology, and previous AV experience. These results provide important references for future implementations of the AV technology. Additionally, based on the inconsistent effects for variables across different models, suggestions for future transportation survey designs are provided.

乘坐体验对自动驾驶汽车安全性看法变化的影响
自动驾驶汽车(AVs)是一项很有前途的新兴技术,可能在不久的将来得到广泛部署。人们对自动驾驶汽车安全性的看法对自动驾驶技术的部署速度和成功至关重要。现有的研究发现,人们对新兴技术的看法可能会随着更多信息的提供而改变。为了在自动驾驶技术背景下研究这一现象,本文进行了真实的自动驾驶实验,收集了可能与人们在没有任何自动驾驶经验的情况下的初始意见和成功乘坐自动驾驶后的意见变化相关的因素。采用考虑数据异质性的有序probit和二元probit模型来估计这些因素对人们初始意见和意见变化的影响。研究发现,人们对自动驾驶汽车安全的初步看法与人们的年龄、个人收入、每月燃料成本、教育经历和以前的自动驾驶汽车经历显著相关。此外,决定人们在成功乘坐自动驾驶汽车后看法变化的因素包括人们的年龄、个人收入、每月燃油成本、每天通勤时间、独自驾驶指标、购买自动驾驶技术的意愿以及之前的自动驾驶体验。这些结果为未来自动驾驶技术的实现提供了重要的参考。此外,基于不同模型中变量的不一致效应,对未来交通调查设计提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
15.20
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