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 behavior 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 behavior modelling, prediction and interaction control.
|Number of pages||21|
|Journal||IEEE Transactions on Intelligent Transportation Systems|
|Early online date||29 Jul 2020|
|Publication status||Published - 1 Oct 2021|
Bibliographical notePublisher Copyright:
© 2000-2011 IEEE.
- autonomous vehicles
- game-theoretic models
- microscopic and macroscopic behavior models
- pedestrian interaction
- signaling models
- trajectory prediction