University of Limerick
Denny_2023_Pedestrian.pdf (3.06 MB)

Pedestrian crossing intention forecasting at unsignalized intersections using naturalistic trajectories

Download (3.06 MB)
journal contribution
posted on 2023-05-15, 15:01 authored by Esteban Moreno, Patrick DennyPatrick Denny, Enda Ward, Jonathan Horgan, CIARAN EISINGCIARAN EISING, Edward Jones, Martin Glavin, Ashkan Parsi, Darragh Mullins, Brian Deegan

Interacting with other roads users is a challenge for an autonomous vehicle, particularly in urban areas. Existing vehicle systems behave in a reactive manner, warning the driver or applying the brakes when the pedestrian is already in front of the vehicle. The ability to anticipate a pedestrian’s crossing intention ahead of time will result in safer roads and smoother vehicle maneuvers. The problem of crossing intent forecasting at intersections is formulated in this paper as a classification task. A model that predicts pedestrian crossing behaviour at different locations around an urban intersection is proposed. The model not only provides a classification label (e.g., crossing, not-crossing), but a quantitative confidence level (i.e., probability). The training and evaluation are carried out using naturalistic trajectories provided by a publicly available dataset recorded from a drone. Results show that the model is able to predict crossing intention within a 3-s time window.


Lero_Phase 2

Science Foundation Ireland

Find out more...



Sensors 2023, 23, 2273



Department or School

  • Electronic & Computer Engineering

Usage metrics

    University of Limerick