公众对互联和自动驾驶汽车的看法:从澳大利亚的视角看联网和自动驾驶汽车的好处、担忧和障碍

Ali Matin;Hussein Dia
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引用次数: 0

摘要

本研究调查了澳大利亚公众对联网和自动驾驶汽车(CAV)的态度和担忧,以及影响他们采用该技术意愿的因素。通过一项综合调查,不同的受访者对各种 CAV 场景提供了宝贵的见解,如乘坐无驾驶员的车辆、自动驾驶公共交通、自动驾驶出租车和无驾驶员的重型车辆。调查结果表明,对自动驾驶汽车的安全担忧对个人在所有场景下的态度都有重大影响。更高的担忧水平与更消极的态度相关联,担忧与反对之间的强相关性强调了消除这些担忧以建立公众信任和促进 CAV 应用的必要性。有趣的是,近 70% 的受访者认为在自动驾驶汽车旁边开车不舒服,但他们对在不久的将来采用自动驾驶公共交通工具表现出更大的信心。此外,约 40% 的受访者表示非常愿意购买 CAV,主要是出于减少碳足迹的愿望和安全考虑。值得注意的是,有健康问题或残疾的受访者对 CAV 技术表现出更大的兴趣(几乎是无健康问题受访者的两倍)。在对 CAV 的态度和偏好方面出现了性别差异,女性对 CAV 的部署表示了更大程度的关注,并认为存在更多障碍。这强调了采用有针对性的方法来解决不同人群的具体问题的重要性。研究还强调,对技术的信任是部署 CAV 的一个重要障碍,在受访者的关注点中名列前茅。为克服这些挑战并促进 CAV 的成功部署,研究提出了各种策略,包括现场演示、自动公共交通专用线路、采用激励措施以及解决责任问题。本研究的结果为政府机构、汽车制造商和利益相关者促进 CAV 的成功实施提供了宝贵的见解。通过了解社会接受度并解决相关问题,决策者可以制定有效的干预措施和政策,确保澳大利亚安全、广泛地采用 CAV。此外,汽车制造商也可以利用这些结果,考虑符合乘客偏好的设计方面,从而促进 CAV 在未来得到更广泛的接受和采用。最后,本研究为了解澳大利亚公众对 CAV 的看法和接受程度做出了重要贡献。通过指导决策和提供战略信息,本研究为将 CAV 更安全、更有效地融入澳大利亚的交通环境奠定了基础。
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Public Perception of Connected and Automated Vehicles: Benefits, Concerns, and Barriers from an Australian Perspective
This study investigates the attitudes and concerns of the Australian public toward connected and autonomous vehicles (CAVs), and the factors influencing their willingness to adopt this technology. Through a comprehensive survey, a diverse group of respondents provided valuable insights toward various CAV scenarios such as riding in a vehicle with no driver, self-driving public transport, self-driving taxis, and heavy vehicles without drivers. The results highlight the significant impact of safety concerns about automated vehicles on individuals' attitudes across all scenarios. Higher levels of concern were associated with more negative attitudes, and a strong correlation between concerns and opposition underlines the necessity of addressing these apprehensions to build public trust and promote CAV adoption. Interestingly, nearly 70% of respondents felt uncomfortable driving next to a CAV, but they displayed more confidence in adopting automated public transport in the near future. Additionally, around 40% of participants indicated a strong willingness to purchase a CAV, primarily driven by the desire to reduce their carbon footprint and safety considerations. Notably, respondents with health conditions or disability exhibited heightened interest (almost double those without health conditions) in CAV technology. Gender differences emerged in attitudes and preferences toward CAVs, with women expressing a greater level of concern and perceiving higher barriers to CAV deployment. This emphasizes the importance of employing targeted approaches to address the specific concerns of different demographics. The study also underscores the role of trust in technology as a significant barrier to CAV deployment, ranking high among respondents' concerns. To overcome these challenges and facilitate successful CAV deployment, various strategies are suggested, including live demonstrations, dedicated routes for automated public transport, adoption incentives, and addressing liability concerns. The findings from this study offer valuable insights for government agencies, vehicle manufacturers, and stakeholders in promoting the successful implementation of CAVs. By understanding societal acceptance and addressing concerns, decision-makers can devise effective interventions and policies to ensure the safe and widespread adoption of CAVs in Australia. Moreover, vehicle manufacturers can leverage these results to consider design aspects that align with passenger preferences, thereby facilitating the broader acceptance and adoption of CAVs in the future. Finally, this research provides a significant contribution to the understanding of public perception and acceptance of CAVs in the Australian context. By guiding decision-making and informing strategies, the study lays the foundation for a safer and more effective integration of CAVs into the country's transportation landscape.
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Front Cover Contents Advancements and Prospects in Multisensor Fusion for Autonomous Driving Extracting Networkwide Road Segment Location, Direction, and Turning Movement Rules From Global Positioning System Vehicle Trajectory Data for Macrosimulation Decision Making and Control of Autonomous Vehicles Under the Condition of Front Vehicle Sideslip
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