论文标题
自动驾驶的行人模型I部分:低级模型,从传感到跟踪
Pedestrian Models for Autonomous Driving Part I: Low-Level Models, from Sensing to Tracking
论文作者
论文摘要
自动驾驶汽车(AV)必须与行人共享空间,包括在行车道案件中,例如行人过境点的汽车和货车外案件,例如送货车辆在人群中导致行人高街道的人群导航。与静态障碍物不同,行人是具有复杂互动运动的活性代理。因此,在行人在场的情况下,计划AV行动需要对其可能的未来行为进行建模以及检测和跟踪。这本叙事评论文章是一对的第一部分,共同调查了当前参与此过程的技术堆栈,将最新的研究组织到了从低级图像检测到高级心理学模型的层次分类法,从AV设计师的角度来看。这个独立的部分I涵盖了该堆栈的较低级别,从感知,检测和识别到跟踪行人。发现这些级别的技术已成熟,可作为用于高级系统的基础,例如行为建模,预测和相互作用控制。
Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles navigating through crowds on pedestrianized high-streets. Unlike static obstacles, pedestrians are active agents with complex, interactive motions. Planning AV actions in the presence of pedestrians thus requires modelling of their probable future behaviour as well as detecting and tracking them. This narrative review article is Part I of a pair, together surveying the current technology stack involved in this process, organising recent research into a hierarchical taxonomy ranging from low-level image detection to high-level psychology models, from the perspective of an AV designer. This self-contained Part I covers the lower levels of this stack, from sensing, through detection and recognition, up to tracking of pedestrians. Technologies at these levels are found to be mature and available as foundations for use in high-level systems, such as behaviour modelling, prediction and interaction control.