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Young people's travel behavior - Using the life-oriented approach to understand the acceptance of autonomous driving

机译：年轻人的出行行为-使用面向生命的方法来了解自动驾驶的接受度

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The self-driving public bus (SDPB) holds the potential to replace human-operated driving with more eco-friendly means and is therefore a valuable mobility solution for our future. The SDPB is based on the innovative technology of autonomous driving, which can only be guaranteed future market success with broad enough user acceptance. This acceptance is thus an essential factor for the growth of SDPB services. In this context, the travel behavior of young people is particularly interesting, as its development will continually demonstrate future mobility behavior trends. However, little research has been conducted regarding the best methods for motivating young people to accept SDPBs as a viable mode of travel.To address this topic, we first conducted a literature review, identifying factors that potentially influence SDPB acceptance. Subsequently, we developed a comprehensive research model based on the life-oriented approach and the technology acceptance model. This conceptualization was validated by a survey of 268 SDPB riders in real-world traffic. The results reveal several novel factors influencing the acceptance of SDPBs, in particular regarding differences in age. Our research contributes to existing research on both the life-oriented and travel behavior approaches by highlighting age differences and their importance in the field. For instance, our findings demonstrate a vital need to account for age differences when deriving policy implications for future mobility solutions.
机译：无人驾驶公共巴士（SDPB）有潜力以更环保的方式取代人工驾驶，因此对于我们的未来来说是宝贵的出行解决方案。 SDPB基于自动驾驶的创新技术，只有在获得足够用户认可的情况下，才能确保其在未来市场上的成功。因此，这种接受是SDPB服务增长的重要因素。在这种情况下，年轻人的出行行为特别有趣，因为其发展将不断显示出未来出行行为的趋势。但是，关于激励年轻人接受SDPB作为一种可行的出行方式的最佳方法的研究很少，为此，我们首先进行了文献综述，确定了可能影响SDPB接受的因素。随后，我们基于面向生命的方法和技术接受模型开发了一个全面的研究模型。通过对268位SDPB骑手在现实世界中的流量进行的调查，验证了这一概念。结果揭示了一些影响SDPB接受的新颖因素，特别是在年龄差异方面。我们的研究通过强调年龄差异及其在该领域的重要性，为有关生活方式和出行行为方法的现有研究做出了贡献。例如，我们的发现表明，在为未来的出行解决方案提供政策含义时，必须考虑年龄差异。

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