当前位置: X-MOL 学术Transportation › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Effects of neighborhood environments on perceived risk of self-driving: evidence from the 2015 and 2017 Puget Sound Travel Surveys
Transportation ( IF 3.5 ) Pub Date : 2019-11-11 , DOI: 10.1007/s11116-019-10069-9
Kailai Wang , Gulsah Akar

Abstract Autonomous vehicles (AVs), with an expectation of improving road safety, are closer to becoming a reality. A large number of people are still concerned about how AVs would operate in real-life driving environments. The present paper investigates the factors that affect people’s views of the interactions between AVs and other road users based on a large sample from the 2015 and 2017 Puget Sound Travel Surveys. We specifically highlight the effects of the neighborhood environment and road infrastructure. We estimate a generalized ordered logit model to demonstrate the extent to which certain neighborhood environment and road infrastructure features affect individuals’ safety perceptions of AVs, controlling for demographics, daily travel patterns, and general interest in riding AVs. The results reveal that designated bicycle facilities are positively associated with individuals’ safety perceptions related to AVs. We find that residents from neighborhoods with more pedestrian facilities are more likely to express higher levels of concern on AVs’ capabilities to react to the environment. Our results also suggest that people living in mixed-use neighborhoods are more confident in sharing the road with AVs. The findings provide useful implications for effective policy interventions and infrastructure provisions that may affect the market penetration rates of AVs while keeping up the standards for other road users, such as bicyclists and pedestrians.

中文翻译:

邻里环境对自动驾驶感知风险的影响:来自 2015 年和 2017 年普吉特海湾旅行调查的证据

摘要 自动驾驶汽车 (AV) 有望改善道路安全,即将成为现实。许多人仍然担心自动驾驶汽车在现实驾驶环境中的运行方式。本文基于 2015 年和 2017 年普吉特海湾旅行调查的大量样本,调查了影响人们对自动驾驶汽车与其他道路使用者之间互动看法的因素。我们特别强调了邻里环境和道路基础设施的影响。我们估计了一个广义有序 logit 模型,以证明某些社区环境和道路基础设施特征在多大程度上影响个人对自动驾驶汽车的安全认知,控制人口统计数据、日常出行模式和对乘坐自动驾驶汽车的普遍兴趣。结果表明,指定的自行车设施与个人对自动驾驶汽车的安全认知呈正相关。我们发现,来自拥有更多步行设施的社区的居民更有可能对自动驾驶汽车对环境的反应能力表示更高水平的关注。我们的结果还表明,居住在混合用途社区的人们对与 AV 共享道路更有信心。研究结果为有效的政策干预和基础设施提供了有用的启示,这些措施可能会影响自动驾驶汽车的市场渗透率,同时保持其他道路使用者(如骑自行车者和行人)的标准。我们发现,来自拥有更多步行设施的社区的居民更有可能对自动驾驶汽车对环境的反应能力表示更高水平的关注。我们的结果还表明,居住在混合用途社区的人们对与 AV 共享道路更有信心。研究结果为有效的政策干预和基础设施提供了有用的启示,这些措施可能会影响自动驾驶汽车的市场渗透率,同时保持其他道路使用者(如骑自行车者和行人)的标准。我们发现,来自拥有更多步行设施的社区的居民更有可能对自动驾驶汽车对环境的反应能力表示更高水平的关注。我们的结果还表明,居住在混合用途社区的人们对与 AV 共享道路更有信心。研究结果为有效的政策干预和基础设施规定提供了有用的启示,这些措施可能会影响自动驾驶汽车的市场渗透率,同时保持其他道路使用者(如骑自行车者和行人)的标准。
更新日期:2019-11-11
down
wechat
bug