[2003.11959] Pedestrian Models for Autonomous Driving Part II: high level models of human behaviour

Autonomous vehicles (AVs) must share space with human pedestrians, both in
on-road cases such as cars at pedestrian crossings and off-road cases such as
delivery vehicles navigating through crowds on high-streets. Unlike static and
kinematic 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 detection and tracking
which enable such modelling. This narrative review article is Part II of a pair
which together survey the current technology stack involved in this process,
organising recent research into a hierarchical taxonomy ranging from low level
image detection to high-level psychological models, from the perspective of an
AV designer. This self-contained Part II covers the higher levels of this
stack, consisting of models of pedestrian behaviour, from prediction of
individual pedestrians’ likely destinations and paths, to game theoretic models
of interactions between pedestrians and autonomous vehicles. This survey
clearly shows that, although there are good models for optimal walking
behaviour, high-level psychological and social modelling of pedestrian
behaviour still remains an open research question that requires many conceptual
issues to be clarified by the community. At these levels, early work has been
done on descriptive and qualitative models of behaviour, but much work is still
needed to translate them into quantitative algorithms for practical AV control.