用自动驾驶车模拟地铁道口行人风险，测试警报系统有效性。
Evaluating Pedestrian Risks in Shared Spaces Through Autonomous Vehicle Experiments on a Fixed Track
- 在固定轨道场景中用自动驾驶车复现行人与电车交互
- 警报系统可有效提升行人对电车通行的识别与反应
- 研究结果适用于无序人行横道的共享空间安全设计
多数自动驾驶安全研究集中于结构化、受控环境，但针对非规制行人区域（尤其是与电车等公共交通互动）的安全研究仍不足。本研究通过在可控环境中使用自动驾驶车辆，复现真实世界中电车与行人交互的场景，评估警报系统的有效性。结果表明，其他场景中的安全措施可被适配应用于有固定轨道的共享空间，其中固定轨道会加剧非规制过街行为带来的风险。研究为城市交通共享空间的安全干预提供了实证支持。
原文摘要 · Abstract (English)
The majority of research on safety in autonomous vehicles has been conducted in structured and controlled environments. However, there is a scarcity of research on safety in unregulated pedestrian areas, especially when interacting with public transport vehicles like trams. This study investigates pedestrian responses to an alert system in this context by replicating this real-world scenario in an environment using an autonomous vehicle. The results show that safety measures from other contexts can be adapted to shared spaces with trams, where fixed tracks heighten risks in unregulated crossings.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。