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.

在交通网络中采用自动驾驶汽车 (AV) 不仅依赖于 AV 用户的技术接受度，还依赖于行人等其他道路用户的技术接受度。然而，之前的研究主要集中在用户对自动驾驶汽车的接受度上，而行人对自动驾驶汽车的接受程度在很大程度上尚未得到探索。本研究旨在通过应用计划行为理论 (TPB)、技术接受模型 (TAM) 和技术接受和使用统一理论 (UTAUT) 来调查行人过马路的意图，从而填补这一空白。完全AV。为了实现这一目标，在澳大利亚进行了 20 分钟的在线问卷调查，并从总共 485 名参与者中收集了数据（平均年龄 = 35.35 岁，51.5% 为女性）。然后对数据应用双变量相关分析和层次回归模型来研究行人属性与其行为意图之间的关联。研究结果显示，TPB 和 UTAUT 分别解释了 46% 和 43% 的在完全自动驾驶汽车前过马路的意图差异，感知行为控制 (PBC) 和主观/社会规范是最重要的独特预测因素分别在 TPB 和 UTAUT 内的意图。然而，TAM 仅解释了在完全自动驾驶汽车前过马路的意图差异的 35%。当添加到层次回归的第 2 步时，年龄占 TAM 预测变量之上的额外方差，表明年轻的参与者报告比年长的参与者更愿意在完全自动驾驶汽车前过马路。当与 TPB 和 UTAUT 的预测因子一起输入时，年龄不是意图的重要预测因子。本研究为使用这些理论模型来理解行人对自动驾驶汽车的接受提供支持。