Environment-aware worker trajectory prediction using surveillance camera on modular construction sites

Qiuling Yang, Q. Mei, Chao Fan, Meng Ma, Xinming Li
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引用次数: 1

Abstract

Modular construction sites are often reported as one of the most hazardous workplaces where the complex environments can lead to near misses and life-threatening collisions. To avoid contact collisions and provide a safe workplace, forecasting workers' trajectories on dynamic construction sites is demanding yet remains challenging. Existing approaches for trajectory prediction are mostly limited to only considering the objects moving information. In this paper, an environment-aware distance worker trajectory prediction model is designed to fully exploit the contextual information on construction sites. Incorporating the interactions among workers and distances between workers and static elements into the prediction model, the proposed approach offers a reliable prediction of worker positions. To further exploit the contextual cues, an environment-aware direction scheme taking directional information of the static elements into account is put forth. Extensive numerical tests on synthetic as well as modular construction datasets showcase the improved prediction performance of the proposed approaches in comparison to several state-of-the-art alternatives.
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基于模块化建筑工地监控摄像头的环境感知工人轨迹预测
模块化建筑工地经常被报道为最危险的工作场所之一,因为复杂的环境可能导致险些失误和危及生命的碰撞。为了避免接触碰撞并提供安全的工作场所,预测动态建筑工地上工人的运动轨迹是一项艰巨的任务,但仍然具有挑战性。现有的轨迹预测方法大多局限于只考虑目标的运动信息。为了充分利用建筑工地的环境信息,设计了一个环境感知的远程工人轨迹预测模型。将工人之间的相互作用以及工人与静态元素之间的距离纳入预测模型,该方法提供了对工人位置的可靠预测。为了进一步利用上下文线索,提出了一种考虑静态元素方向信息的环境感知方向方案。在合成和模块化建筑数据集上进行的大量数值测试表明,与几种最先进的替代方法相比,所提出的方法的预测性能有所提高。
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