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安全システム/知覚arXiv:2412.18189

移動作業帯のトラック搭載型衝突緩衝装置に向けた自動・能動的安全警告システムの開発

Toward an Automated, Proactive Safety Warning System Development for Truck Mounted Attenuators in Mobile Work Zones

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ROS上にパノプティック運転知覚アルゴリズムを統合し、衝突コース上の車両を検知して警告する能動的安全システムを実験室環境で実証した。

著者: Xiang Yu, Linlin Zhang, Yaw, Adu-Gyamfi

分類: cs.RO

原文アブストラクト

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.

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