Pedestrian Models for Autonomous Driving Part I: Low-Level Models, from Sensing to Tracking

Fanta Camara*, Nicola Bellotto, Serhan Cosar, Dimitris Nathanael, Matthias Althoff, Jingyuan Wu, Johannes Ruenz, Andre Dietrich, Charles W. Fox

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review


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.

Original languageEnglish
Pages (from-to)6131-6151
Number of pages21
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number10
Early online date29 Jul 2020
Publication statusPublished - 1 Oct 2021

Bibliographical note

Publisher Copyright:
© 2000-2011 IEEE.


  • autonomous vehicles
  • datasets
  • detection
  • eHMI
  • game-theoretic models
  • microscopic and macroscopic behavior models
  • pedestrian interaction
  • pedestrians
  • Review
  • sensing
  • signaling models
  • survey
  • tracking
  • trajectory prediction

Cite this