Public acceptance of conditionally automated vehicles is a crucial step in the realization of smart cities. Prior research in Europe has shown that the factors of hedonic motivation, social influence, and performance expectancy, in decreasing order of importance, influence acceptance. Moreover, a generally positive acceptance of the technology was reported. However, there is a lack of information regarding the public acceptance of conditionally automated vehicles in the United States. In this study, we carried out a web-based experiment where participants were provided information regarding the technology and then completed a questionnaire on their perceptions. The collected data was analyzed using PLS-SEM to examine the factors that may lead to public acceptance of the technology in the United States. Our findings showed that social influence, performance expectancy, effort expectancy, hedonic motivation, and facilitating conditions determine conditionally automated vehicle acceptance. Additionally, certain factors were found to influence the perception of how useful the technology is, the effort required to use it, and the facilitating conditions for its use. By integrating the insights gained from this study, stakeholders can better facilitate the adoption of autonomous vehicle technology, contributing to safer, more efficient, and user-friendly transportation systems in the future that help realize the vision of the smart city.

翻译：公众对有条件的自动化车辆的接受度是实现智慧城市的关键步骤。先前欧洲的研究表明，享乐动机、社会影响、绩效期望这些因素按照重要性递减的顺序影响接受度，且该技术总体上获得了积极接受。然而，关于美国公众对有条件的自动化车辆接受度的信息仍较为匮乏。本研究开展了一项基于网络的实验，参与者首先获得相关技术信息，随后完成关于其感知的问卷调查。采用PLS-SEM对收集的数据进行分析，以探究可能导致美国公众接受该技术的因素。研究结果表明，社会影响、绩效期望、努力期望、享乐动机和促进条件决定了有条件的自动化车辆的接受度。此外，某些因素还会影响人们对技术有用性、使用所需努力以及促进条件的感知。通过整合本研究的见解，利益相关者可以更好地促进自动驾驶技术的采用，从而构建更安全、高效且用户友好的未来交通系统，助力实现智慧城市的愿景。