15 citations · 61 across the 17 of their papers we have counts for
4 papers · 1 filter
Predicting Vehicles Trajectories in Urban Scenarios with Transformer Networks and Augmented Information
A. Quintanar, D. Fernández-Llorca, I. Parra +2
Understanding the behavior of road users is of vital importance for the development of trajectory prediction systems. In this context, the latest advances have focused on recurrent…
IntFormer: Predicting pedestrian intention with the aid of the Transformer architecture
J. Lorenzo, I. Parra, M. A. Sotelo
Understanding pedestrian crossing behavior is an essential goal in intelligent vehicle development, leading to an improvement in their security and traffic flow. In this paper, we…
Model Guided Road Intersection Classification
Augusto Luis Ballardini, Álvaro Hernández, Miguel Ángel Sotelo
Understanding complex scenarios from in-vehicle cameras is essential for safely operating autonomous driving systems in densely populated areas. Among these, intersection areas are…
SCOUT: Socially-COnsistent and UndersTandable Graph Attention Network for Trajectory Prediction of Vehicles and VRUs
Sandra Carrasco, David Fernández Llorca, Miguel Ángel Sotelo
Autonomous vehicles navigate in dynamically changing environments under a wide variety of conditions, being continuously influenced by surrounding objects. Modelling interactions a…