14 citations · 44 across the 14 of their papers we have counts for
15 papers
Realistic pedestrian behaviour in the CARLA simulator using VR and mocap
Sergio Martín Serrano, David Fernández Llorca, Iván García Daza +1
Simulations are gaining increasingly significance in the field of autonomous driving due to the demand for rapid prototyping and extensive testing. Employing physics-based simulati…
Digital twin in virtual reality for human-vehicle interactions in the context of autonomous driving
Sergio Martín Serrano, Rubén Izquierdo, Iván García Daza +2
This paper presents the results of tests of interactions between real humans and simulated vehicles in a virtual scenario. Human activity is inserted into the virtual world via a v…
Towards Explainable Motion Prediction using Heterogeneous Graph Representations
Sandra Carrasco Limeros, Sylwia Majchrowska, Joakim Johnander +2
Motion prediction systems aim to capture the future behavior of traffic scenarios enabling autonomous vehicles to perform safe and efficient planning. The evolution of these scenar…
Towards trustworthy multi-modal motion prediction: Holistic evaluation and interpretability of outputs
Sandra Carrasco Limeros, Sylwia Majchrowska, Joakim Johnander +3
Predicting the motion of other road agents enables autonomous vehicles to perform safe and efficient path planning. This task is very complex, as the behaviour of road agents depen…
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…
Towards view-invariant vehicle speed detection from driving simulator images
Antonio Hernández Martínez, David Fernandez Llorca, Iván García Daza
The use of cameras for vehicle speed measurement is much more cost effective compared to other technologies such as inductive loops, radar or laser. However, accurate speed measure…
Insertion of real agents behaviors in CARLA autonomous driving simulator
Sergio Martín Serrano, David Fernández Llorca, Iván García Daza +1
The role of simulation in autonomous driving is becoming increasingly important due to the need for rapid prototyping and extensive testing. The use of physics-based simulation inv…
Testing predictive automated driving systems: lessons learned and future recommendations
Rubén Izquierdo Gonzalo, Carlota Salinas Maldonado, Javier Alonso Ruiz +3
Conventional vehicles are certified through classical approaches, where different physical certification tests are set up on test tracks to assess required safety levels. These app…
Data-driven vehicle speed detection from synthetic driving simulator images
Antonio Hernández Martínez, Javier Lorenzo Díaz, Iván García Daza +1
Despite all the challenges and limitations, vision-based vehicle speed detection is gaining research interest due to its great potential benefits such as cost reduction, and enhanc…
From driving automation systems to autonomous vehicles: clarifying the terminology
David Fernández Llorca
The terminological landscape is rather cluttered when referring to autonomous driving or vehicles. A plethora of terms are used interchangeably, leading to misuse and confusion. Wi…
Fail-Aware LIDAR-Based Odometry for Autonomous Vehicles
Iván García Daza, Monica Rentero, Carlota Salinas Maldonado +4
Autonomous driving systems are set to become a reality in transport systems and, so, maximum acceptance is being sought among users. Currently, the most advanced architectures requ…
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…
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…