改善短期施工现场人员和车辆的安全状况

IF 4.6 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Open Journal of Intelligent Transportation Systems Pub Date : 2024-02-19 DOI:10.1109/OJITS.2024.3366708
Daniel Rau;Jonas Vogt;Philipp Schorr;Juri Golanov;Andreas Otte;Jens Staub;Horst Wieker
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引用次数: 0

摘要

尽管为加强安全做出了种种努力,但建筑工地仍然是交通事故的主要发生地。特别是短期建筑工地,由于时间紧迫,在实施广泛的安全措施方面面临着限制。本文旨在通过提醒维护人员和驶近的车辆注意潜在的危险情况,来加强短期施工现场的安全。该方法侧重于定义静态建筑工地的精确尺寸,采用高精度实时导航卫星系统(Real-Time-Kinematics-GNSS)定位交通锥,并通过相应的算法得出建筑工地的几何形状。通过分析几何图形,我们可以识别出维护人员靠近活动车道或车辆进入施工现场的情况。为了提高对危险情况的认识,我们介绍了向维护人员和车辆发布信息的方法,以及警告相关人员的技术解决方案。此外,我们还讨论了施工现场的几何形状在驶近车辆中的分布情况,这可以为未来的自动驾驶车辆提供有关施工现场确切起点和终点的重要信息。
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Safety Improvements for Personnel and Vehicles in Short-Term Construction Sites
Despite all efforts to enhance safety, construction sites remain a major location for traffic accidents. Short-term construction sites, in particular, face limitations in implementing extensive safety measures due to their condensed timelines. This paper seeks to enhance safety in short-term construction sites by alerting maintenance personnel and approaching vehicles to potentially dangerous scenarios. Focusing on defining the exact dimensions of static construction sites, this method employs high-precision Real-Time-Kinematics-GNSS for localizing traffic cones and deriving the construction site geometry through respective algorithms. By analyzing the geometry, we can identify situations where maintenance personnel are in close proximity to the active lane or when vehicles enter the construction site. To increase awareness of hazardous situations, we present methods for distributing information to maintenance personnel and vehicles, along with technical solutions for warning those involved. Additionally, we discuss the distribution of the construction site’s geometry among approaching vehicles, which can provide future automated vehicles with crucial information on the site’s exact start and end points.
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