  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.
