55 citations · 88 across the 11 of their papers we have counts for
11 papers
Attribute Annotation and Bias Evaluation in Visual Datasets for Autonomous Driving
David Fernández Llorca, Pedro Frau, Ignacio Parra +2
This paper addresses the often overlooked issue of fairness in the autonomous driving domain, particularly in vision-based perception and prediction systems, which play a pivotal r…
Human-vehicle interaction for autonomous vehicles in crosswalk scenarios: Field experiments with pedestrians and passengers
R. Izquierdo, S. Martín, J. Alonso +3
This paper presents the results of real-world testing of human-vehicle interactions with an autonomous vehicle equipped with internal and external Human Machine Interfaces (HMIs) i…
Vehicle Trajectory Prediction on Highways Using Bird Eye View Representations and Deep Learning
Rubén Izquierdo, Álvaro Quintanar, David Fernández Llorca +4
This work presents a novel method for predicting vehicle trajectories in highway scenarios using efficient bird's eye view representations and convolutional neural networks. Vehicl…
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…
WiFiNet: WiFi-based indoor localisation using CNNs
Noelia Hernández, Ignacio Parra, Héctor Corrales +4
Different technologies have been proposed to provide indoor localisation: magnetic field, bluetooth , WiFi, etc. Among them, WiFi is the one with the highest availability and highe…
The PREVENTION Challenge: How Good Are Humans Predicting Lane Changes?
A. Quintanar, R. Izquierdo, I. Parra +2
While driving on highways, every driver tries to be aware of the behavior of surrounding vehicles, including possible emergency braking, evasive maneuvers trying to avoid obstacles…
3D-DEEP: 3-Dimensional Deep-learning based on elevation patterns forroad scene interpretation
A. Hernández, S. Woo, H. Corrales +4
Road detection and segmentation is a crucial task in computer vision for safe autonomous driving. With this in mind, a new net architecture (3D-DEEP) and its end-to-end training me…
RNN-based Pedestrian Crossing Prediction using Activity and Pose-related Features
Javier Lorenzo, Ignacio Parra, Florian Wirth +3
Pedestrian crossing prediction is a crucial task for autonomous driving. Numerous studies show that an early estimation of the pedestrian's intention can decrease or even avoid a h…
Vehicle Trajectory Prediction in Crowded Highway Scenarios Using Bird Eye View Representations and CNNs
R. Izquierdo, A. Quintanar, I. Parra +2
This paper describes a novel approach to perform vehicle trajectory predictions employing graphic representations. The vehicles are represented using Gaussian distributions into a…
Vehicle Ego-Lane Estimation with Sensor Failure Modeling
Augusto Luis Ballardini, Daniele Cattaneo, Rubén Izquierdo +4
We present a probabilistic ego-lane estimation algorithm for highway-like scenarios that is designed to increase the accuracy of the ego-lane estimate, which can be obtained relyin…