Getting in the path of the robot: Pedestrians acceptance of crossing roads near fully automated vehicles. Kaye, S., Li, X., Oviedo-Trespalacios, O., & Pooyan Afghari, A. Travel Behaviour and Society, 26:1–8, January, 2022. ![Getting in the path of the robot: Pedestrians acceptance of crossing roads near fully automated vehicles [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Adoption of Automated Vehicles (AVs) within transport networks relies on the technology acceptance of not only AV users, but also other road users such as pedestrians. However, previous research has mostly focused on user acceptance of AVs and the receptivity of pedestrians towards AVs has been largely unexplored. This study aims to fill this gap by applying the Theory of Planned Behaviour (TPB), the Technology Acceptance Model (TAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT) to investigate pedestrians’ intentions to cross a road in front of a fully AV. To achieve this goal, a 20-minute online questionnaire was administered in Australia and data were collected from a total of 485 participants (average age = 35.35 years, 51.5% female). Bivariate correlation analysis and hierarchical regression models were then applied on the data to investigate the association between pedestrian attributes and their behavioural intentions. The findings revealed that the TPB and the UTAUT explained 46% and 43% of the variance in intentions to cross a road in front of a fully AV, respectively, with perceived behavioural control (PBC) and subjective/social norms the most significant unique predictors of intentions within the TPB and UTAUT, respectively. The TAM, however, only explained 35% of the variance in intentions to cross a road in front of a fully AV. When added into Step 2 of the hierarchical regression, age accounted for additional variance above the TAM predictors, indicating that younger participants reported higher intentions to cross a road in front of a fully AV than older participants. Age was not a significant predictor of intentions when entered with the predictors of the TPB and UTAUT. This study provides support for the use of these theoretical models to understand pedestrians’ acceptance of AVs. 【摘要翻译】运输网络中采用自动车辆（AV）不仅取决于AV用户的技术接受，还取决于其他道路使用者（例如行人）的接受。但是，以前的研究主要集中在用户接受AV，而行人对AVS的接受程度在很大程度上尚未探索。这项研究旨在通过应用计划行为理论（TPB），技术接受模型（TAM）和统一的技术接受和使用理论（UTAUT）来调查行人在前方道路上的意图来填补这一空白。完全的AV。为了实现这一目标，在澳大利亚进行了20分钟的在线调查表，并从总共485名参与者（平均年龄= 35.35岁为51.5％的女性）中收集了数据。然后将双变量相关分析和分层回归模型应用于数据，以研究行人属性及其行为意图之间的关联。研究结果表明，TPB和UTAUT解释了分别具有可感知的行为控制（PBC）和最重要的独特预测指标的意图的46％和43％的差异。 TPB和UTAUT内的意图。然而，TAM仅解释了在完全AV前的道路上越过道路的35％的差异。当添加到层次回归的步骤2中时，年龄在TAM预测因子上方的额外差异占了额外的差异，这表明年轻的参与者报告说，与年龄较大的参与者相比，年轻的参与者的跨越了完全AV前的道路的意图。当使用TPB和UTAUT的预测指标输入时，年龄并不是意图的重要预测指标。这项研究为使用这些理论模型的使用提供了支持，以了解行人对AV的接受。
@article{kaye_getting_2022,
title = {Getting in the path of the robot: {Pedestrians} acceptance of crossing roads near fully automated vehicles},
volume = {26},
issn = {2214-367X},
shorttitle = {进入机器人的道路：行人在全自动车辆附近的穿越道路},
url = {https://www.sciencedirect.com/science/article/pii/S2214367X21000740},
doi = {10.1016/j.tbs.2021.07.012},
abstract = {Adoption of Automated Vehicles (AVs) within transport networks relies on the technology acceptance of not only AV users, but also other road users such as pedestrians. However, previous research has mostly focused on user acceptance of AVs and the receptivity of pedestrians towards AVs has been largely unexplored. This study aims to fill this gap by applying the Theory of Planned Behaviour (TPB), the Technology Acceptance Model (TAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT) to investigate pedestrians’ intentions to cross a road in front of a fully AV. To achieve this goal, a 20-minute online questionnaire was administered in Australia and data were collected from a total of 485 participants (average age = 35.35 years, 51.5\% female). Bivariate correlation analysis and hierarchical regression models were then applied on the data to investigate the association between pedestrian attributes and their behavioural intentions. The findings revealed that the TPB and the UTAUT explained 46\% and 43\% of the variance in intentions to cross a road in front of a fully AV, respectively, with perceived behavioural control (PBC) and subjective/social norms the most significant unique predictors of intentions within the TPB and UTAUT, respectively. The TAM, however, only explained 35\% of the variance in intentions to cross a road in front of a fully AV. When added into Step 2 of the hierarchical regression, age accounted for additional variance above the TAM predictors, indicating that younger participants reported higher intentions to cross a road in front of a fully AV than older participants. Age was not a significant predictor of intentions when entered with the predictors of the TPB and UTAUT. This study provides support for the use of these theoretical models to understand pedestrians’ acceptance of AVs.
【摘要翻译】运输网络中采用自动车辆（AV）不仅取决于AV用户的技术接受，还取决于其他道路使用者（例如行人）的接受。但是，以前的研究主要集中在用户接受AV，而行人对AVS的接受程度在很大程度上尚未探索。这项研究旨在通过应用计划行为理论（TPB），技术接受模型（TAM）和统一的技术接受和使用理论（UTAUT）来调查行人在前方道路上的意图来填补这一空白。完全的AV。为了实现这一目标，在澳大利亚进行了20分钟的在线调查表，并从总共485名参与者（平均年龄= 35.35岁为51.5％的女性）中收集了数据。然后将双变量相关分析和分层回归模型应用于数据，以研究行人属性及其行为意图之间的关联。研究结果表明，TPB和UTAUT解释了分别具有可感知的行为控制（PBC）和最重要的独特预测指标的意图的46％和43％的差异。 TPB和UTAUT内的意图。然而，TAM仅解释了在完全AV前的道路上越过道路的35％的差异。当添加到层次回归的步骤2中时，年龄在TAM预测因子上方的额外差异占了额外的差异，这表明年轻的参与者报告说，与年龄较大的参与者相比，年轻的参与者的跨越了完全AV前的道路的意图。当使用TPB和UTAUT的预测指标输入时，年龄并不是意图的重要预测指标。这项研究为使用这些理论模型的使用提供了支持，以了解行人对AV的接受。},
language = {en},
urldate = {2022-12-06},
journal = {Travel Behaviour and Society},
author = {Kaye, Sherrie-Anne and Li, Xiaomeng and Oviedo-Trespalacios, Oscar and Pooyan Afghari, Amir},
month = jan,
year = {2022},
keywords = {/unread, Automated vehicles, Pedestrians, Technology acceptance, Technology acceptance model, Theory of planned behaviour, Unified theory of acceptance and use of technology},
pages = {1--8},
}
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This study aims to fill this gap by applying the Theory of Planned Behaviour (TPB), the Technology Acceptance Model (TAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT) to investigate pedestrians’ intentions to cross a road in front of a fully AV. To achieve this goal, a 20-minute online questionnaire was administered in Australia and data were collected from a total of 485 participants (average age = 35.35 years, 51.5% female). Bivariate correlation analysis and hierarchical regression models were then applied on the data to investigate the association between pedestrian attributes and their behavioural intentions. The findings revealed that the TPB and the UTAUT explained 46% and 43% of the variance in intentions to cross a road in front of a fully AV, respectively, with perceived behavioural control (PBC) and subjective/social norms the most significant unique predictors of intentions within the TPB and UTAUT, respectively. The TAM, however, only explained 35% of the variance in intentions to cross a road in front of a fully AV. When added into Step 2 of the hierarchical regression, age accounted for additional variance above the TAM predictors, indicating that younger participants reported higher intentions to cross a road in front of a fully AV than older participants. Age was not a significant predictor of intentions when entered with the predictors of the TPB and UTAUT. This study provides support for the use of these theoretical models to understand pedestrians’ acceptance of AVs. 【摘要翻译】运输网络中采用自动车辆（AV）不仅取决于AV用户的技术接受，还取决于其他道路使用者（例如行人）的接受。但是，以前的研究主要集中在用户接受AV，而行人对AVS的接受程度在很大程度上尚未探索。这项研究旨在通过应用计划行为理论（TPB），技术接受模型（TAM）和统一的技术接受和使用理论（UTAUT）来调查行人在前方道路上的意图来填补这一空白。完全的AV。为了实现这一目标，在澳大利亚进行了20分钟的在线调查表，并从总共485名参与者（平均年龄= 35.35岁为51.5％的女性）中收集了数据。然后将双变量相关分析和分层回归模型应用于数据，以研究行人属性及其行为意图之间的关联。研究结果表明，TPB和UTAUT解释了分别具有可感知的行为控制（PBC）和最重要的独特预测指标的意图的46％和43％的差异。 TPB和UTAUT内的意图。然而，TAM仅解释了在完全AV前的道路上越过道路的35％的差异。当添加到层次回归的步骤2中时，年龄在TAM预测因子上方的额外差异占了额外的差异，这表明年轻的参与者报告说，与年龄较大的参与者相比，年轻的参与者的跨越了完全AV前的道路的意图。当使用TPB和UTAUT的预测指标输入时，年龄并不是意图的重要预测指标。这项研究为使用这些理论模型的使用提供了支持，以了解行人对AV的接受。","language":"en","urldate":"2022-12-06","journal":"Travel Behaviour and Society","author":[{"propositions":[],"lastnames":["Kaye"],"firstnames":["Sherrie-Anne"],"suffixes":[]},{"propositions":[],"lastnames":["Li"],"firstnames":["Xiaomeng"],"suffixes":[]},{"propositions":[],"lastnames":["Oviedo-Trespalacios"],"firstnames":["Oscar"],"suffixes":[]},{"propositions":[],"lastnames":["Pooyan","Afghari"],"firstnames":["Amir"],"suffixes":[]}],"month":"January","year":"2022","keywords":"/unread, Automated vehicles, Pedestrians, Technology acceptance, Technology acceptance model, Theory of planned behaviour, Unified theory of acceptance and use of technology","pages":"1–8","bibtex":"@article{kaye_getting_2022,\n\ttitle = {Getting in the path of the robot: {Pedestrians} acceptance of crossing roads near fully automated vehicles},\n\tvolume = {26},\n\tissn = {2214-367X},\n\tshorttitle = {进入机器人的道路：行人在全自动车辆附近的穿越道路},\n\turl = {https://www.sciencedirect.com/science/article/pii/S2214367X21000740},\n\tdoi = {10.1016/j.tbs.2021.07.012},\n\tabstract = {Adoption of Automated Vehicles (AVs) within transport networks relies on the technology acceptance of not only AV users, but also other road users such as pedestrians. However, previous research has mostly focused on user acceptance of AVs and the receptivity of pedestrians towards AVs has been largely unexplored. This study aims to fill this gap by applying the Theory of Planned Behaviour (TPB), the Technology Acceptance Model (TAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT) to investigate pedestrians’ intentions to cross a road in front of a fully AV. To achieve this goal, a 20-minute online questionnaire was administered in Australia and data were collected from a total of 485 participants (average age = 35.35 years, 51.5\\% female). Bivariate correlation analysis and hierarchical regression models were then applied on the data to investigate the association between pedestrian attributes and their behavioural intentions. The findings revealed that the TPB and the UTAUT explained 46\\% and 43\\% of the variance in intentions to cross a road in front of a fully AV, respectively, with perceived behavioural control (PBC) and subjective/social norms the most significant unique predictors of intentions within the TPB and UTAUT, respectively. The TAM, however, only explained 35\\% of the variance in intentions to cross a road in front of a fully AV. When added into Step 2 of the hierarchical regression, age accounted for additional variance above the TAM predictors, indicating that younger participants reported higher intentions to cross a road in front of a fully AV than older participants. Age was not a significant predictor of intentions when entered with the predictors of the TPB and UTAUT. This study provides support for the use of these theoretical models to understand pedestrians’ acceptance of AVs.\n\n【摘要翻译】运输网络中采用自动车辆（AV）不仅取决于AV用户的技术接受，还取决于其他道路使用者（例如行人）的接受。但是，以前的研究主要集中在用户接受AV，而行人对AVS的接受程度在很大程度上尚未探索。这项研究旨在通过应用计划行为理论（TPB），技术接受模型（TAM）和统一的技术接受和使用理论（UTAUT）来调查行人在前方道路上的意图来填补这一空白。完全的AV。为了实现这一目标，在澳大利亚进行了20分钟的在线调查表，并从总共485名参与者（平均年龄= 35.35岁为51.5％的女性）中收集了数据。然后将双变量相关分析和分层回归模型应用于数据，以研究行人属性及其行为意图之间的关联。研究结果表明，TPB和UTAUT解释了分别具有可感知的行为控制（PBC）和最重要的独特预测指标的意图的46％和43％的差异。 TPB和UTAUT内的意图。然而，TAM仅解释了在完全AV前的道路上越过道路的35％的差异。当添加到层次回归的步骤2中时，年龄在TAM预测因子上方的额外差异占了额外的差异，这表明年轻的参与者报告说，与年龄较大的参与者相比，年轻的参与者的跨越了完全AV前的道路的意图。当使用TPB和UTAUT的预测指标输入时，年龄并不是意图的重要预测指标。这项研究为使用这些理论模型的使用提供了支持，以了解行人对AV的接受。},\n\tlanguage = {en},\n\turldate = {2022-12-06},\n\tjournal = {Travel Behaviour and Society},\n\tauthor = {Kaye, Sherrie-Anne and Li, Xiaomeng and Oviedo-Trespalacios, Oscar and Pooyan Afghari, Amir},\n\tmonth = jan,\n\tyear = {2022},\n\tkeywords = {/unread, Automated vehicles, Pedestrians, Technology acceptance, Technology acceptance model, Theory of planned behaviour, Unified theory of acceptance and use of technology},\n\tpages = {1--8},\n}\n\n","author_short":["Kaye, S.","Li, X.","Oviedo-Trespalacios, O.","Pooyan Afghari, A."],"key":"kaye_getting_2022","id":"kaye_getting_2022","bibbaseid":"kaye-li-oviedotrespalacios-pooyanafghari-gettinginthepathoftherobotpedestriansacceptanceofcrossingroadsnearfullyautomatedvehicles-2022","role":"author","urls":{"Paper":"https://www.sciencedirect.com/science/article/pii/S2214367X21000740"},"keyword":["/unread","Automated vehicles","Pedestrians","Technology acceptance","Technology acceptance model","Theory of planned behaviour","Unified theory of acceptance and use of technology"],"metadata":{"authorlinks":{}},"html":""},"bibtype":"article","biburl":"https://bibbase.org/zotero/_MingYAN_","dataSources":["7bvyz9GrWb3E3F8y3"],"keywords":["/unread","automated vehicles","pedestrians","technology acceptance","technology acceptance model","theory of planned behaviour","unified theory of acceptance and use of technology"],"search_terms":["getting","path","robot","pedestrians","acceptance","crossing","roads","near","fully","automated","vehicles","kaye","li","oviedo-trespalacios","pooyan afghari"],"title":"Getting in the path of the robot: Pedestrians acceptance of crossing roads near fully automated vehicles","year":2022}