为移动施工区的防撞车设计主动预警系统，提升道路安全。
Toward an Automated, Proactive Safety Warning System Development for Truck Mounted Attenuators in Mobile Work Zones
- 将全景驾驶感知算法集成到ROS系统中，实现实时车辆追踪与预警。
- 实验表明系统可实时计算距离与速度并触发警告信号。
- 适合交通工程、智能驾驶安全领域研究者参考。
尽管卡车安装式缓冲器（TMA）/自动驾驶卡车安装式缓冲器（ATMA）及交通管控设备在移动施工区应用日益广泛，但施工区碰撞事故仍是美国的重大安全隐患。2023年密苏里州发生63起与TMA相关的车祸，较2022年上升27%。目前所有施工区标志均为被动安全措施，依赖驾驶员识别与注意力，部分分心驾驶员可能忽略警示，带来安全风险。本研究提出一种附加的主动预警系统，可集成于TMA/ATMA，提升整体安全性。通过将全景驾驶感知算法嵌入机器人操作系统（ROS），实现了对碰撞路径车辆的实时预警。实验在实验室环境中使用两台ROS机器人和桌面级GPU进行，验证了系统实时计算距离与速度并激活警报信号的能力。利用ROS的分布式计算特性，支持灵活部署并降低成本。未来实地测试中，结合AASHTO绿皮书规定的停止视距（SSD）标准，系统将实现对来车的实时监控，并提供主动预警，进一步提升移动施工区的安全性。
原文摘要 · Abstract (English)
Even though Truck Mounted Attenuators (TMA)/Autonomous Truck Mounted Attenuators (ATMA) and traffic control devices are increasingly used in mobile work zones to enhance safety, work zone collisions remain a significant safety concern in the United States. In Missouri, there were 63 TMA-related crashes in 2023, a 27% increase compared to 2022. Currently, all the signs in the mobile work zones are passive safety measures, relying on drivers' recognition and attention. Some distracted drivers may ignore these signs and warnings, raising safety concerns. In this study, we proposed an additional proactive warning system that could be applied to the TMA/ATMA to improve overall safety. A feasible solution has been demonstrated by integrating a Panoptic Driving Perception algorithm into the Robot Operating System (ROS) and applying it to the TMA/ATMA systems. This enables us to alert vehicles on a collision course with the TMA. Our experimental setup, currently conducted in a laboratory environment with two ROS robots and a desktop GPU, demonstrates the system's capability to calculate real-time distance and speed and activate warning signals. Leveraging ROS's distributed computing capabilities allows for flexible system deployment and cost reduction. In future field tests, by combining the stopping sight distance (SSD) standards from the AASHTO Green Book, the system enables real-time monitoring of oncoming vehicles and provides additional proactive warnings to enhance the safety of mobile work zones.
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。