Pedestrian Models for Autonomous Driving Part I: Low-Level Models, from Sensing to Tracking
It addresses the problem of enabling autonomous vehicles to interact safely with pedestrians, but it is incremental as it synthesizes existing research without introducing new methods.
The paper reviews low-level pedestrian modeling technologies for autonomous vehicles, covering sensing, detection, recognition, and tracking, and finds these technologies to be mature and ready for use in higher-level systems.
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.