With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand, and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots, and advanced surveillance systems. This article provides a survey of human motion trajectory prediction. We review, analyze, and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.

中文翻译：

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人体运动轨迹预测：调查

随着人类环境中智能自主系统的数量不断增加，此类系统感知、理解和预测人类行为的能力变得越来越重要。具体而言，预测动态代理的未来位置并考虑此类预测进行规划是自动驾驶汽车、服务机器人和先进监控系统的关键任务。本文提供了人体运动轨迹预测的综述。我们审查、分析和构建来自不同社区的大量工作，并提出了一种分类法，该分类法根据运动建模方法和所使用的上下文信息级别对现有方法进行分类。我们提供了现有数据集和性能指标的概述。我们讨论了现有技术的局限性并概述了进一步研究的方向。