Fuad Yasin Huda , Graham Currie , Liton Kamruzzaman
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Income was found to have the greatest effect on AV VOT, followed by geographical location and driver’s licence. High-income people, residents in urban areas, and people without driving licence place a higher VOT for AV travel – i.e., these groups are willing to pay more for reducing one unit of their travel time. High-income individuals are willing to pay AU$8 more per hour than low-income individuals, urban residents are willing to pay AU$6.5 more per hour than rural residents, and people without a driving licence are willing to pay AU$3.7 more per hour than those with one. Results aid future research in two ways: identifying factors that could impact the value of travel time for AVs and guiding the design of experimental setups for future AV VOT estimates. Additionally, results will help policymakers assess the benefits and costs of implementing AV-related policies in different contexts.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"39 ","pages":"Article 100958"},"PeriodicalIF":5.1000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measuring the relative impact of factors influencing autonomous vehicle value of travel time\",\"authors\":\"Fuad Yasin Huda , Graham Currie , Liton Kamruzzaman\",\"doi\":\"10.1016/j.tbs.2024.100958\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Value of travel time (VOT) serves as a crucial metric for understanding the benefits of transport investments and policy initiatives. 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引用次数: 0
摘要
旅行时间价值(VOT)是了解交通投资和政策措施效益的重要指标。尽管有许多研究对自动驾驶汽车(AV)的出行时间价值进行了估算,但仍未达成共识,影响自动驾驶汽车出行时间价值估算的因素的可变性也有待深入探讨。本研究通过对 24 项已发表研究中的自动驾驶汽车 VOT 估计值进行元回归分析,弥补了这些不足。通过对文献的系统回顾,确定了 22 个可能影响 AV VOT 估计值的因素。在控制其他因素影响的情况下,估算了每个因素对 AV VOT 的相对影响。结果显示,有八个因素对 AV VOT 有显著的统计影响。收入对 AV VOT 的影响最大,其次是地理位置和驾照。高收入人群、城市居民和无驾驶执照者对自动驾驶汽车出行的 VOT 值较高,即这些人群愿意为减少一个单位的出行时间支付更多费用。高收入人群愿意比低收入人群每小时多支付 8 澳元,城市居民愿意比农村居民每小时多支付 6.5 澳元,无驾照人群愿意比有驾照人群每小时多支付 3.7 澳元。研究结果对未来的研究有两方面的帮助:一是确定可能影响自动驾驶汽车旅行时间价值的因素,二是指导未来自动驾驶汽车VOT估算的实验设计。此外,研究结果还有助于政策制定者评估在不同情况下实施与自动驾驶汽车相关政策的收益和成本。
Measuring the relative impact of factors influencing autonomous vehicle value of travel time
Value of travel time (VOT) serves as a crucial metric for understanding the benefits of transport investments and policy initiatives. Despite numerous studies estimating the VOT for Autonomous Vehicles (AVs), consensus remains elusive, and the variability of the factors influencing AV VOT estimates has yet to be thoroughly explored. This study addresses these gaps through a meta-regression analysis of AV VOT estimates drawn from 24 published studies. 22 factors were identified, through a systematic review of the literature, likely to affect AV VOT estimates. The relative impact of each of the factors on AV VOT were estimated, controlling for the effects of other factors. Results show that eight factors have a statistically significant effect on AV VOT. Income was found to have the greatest effect on AV VOT, followed by geographical location and driver’s licence. High-income people, residents in urban areas, and people without driving licence place a higher VOT for AV travel – i.e., these groups are willing to pay more for reducing one unit of their travel time. High-income individuals are willing to pay AU$8 more per hour than low-income individuals, urban residents are willing to pay AU$6.5 more per hour than rural residents, and people without a driving licence are willing to pay AU$3.7 more per hour than those with one. Results aid future research in two ways: identifying factors that could impact the value of travel time for AVs and guiding the design of experimental setups for future AV VOT estimates. Additionally, results will help policymakers assess the benefits and costs of implementing AV-related policies in different contexts.
期刊介绍:
Travel Behaviour and Society is an interdisciplinary journal publishing high-quality original papers which report leading edge research in theories, methodologies and applications concerning transportation issues and challenges which involve the social and spatial dimensions. In particular, it provides a discussion forum for major research in travel behaviour, transportation infrastructure, transportation and environmental issues, mobility and social sustainability, transportation geographic information systems (TGIS), transportation and quality of life, transportation data collection and analysis, etc.