Javier Araluce
YOU?
Author Swipe
A Fallback Localization Algorithm for Automated Vehicles Based on Object Detection and Tracking Open
Integrating Automated Vehicles (AVs) into everyday traffic is an ongoing challenge. Ensuring the safety of all involved agents, even in the presence of system failures, is crucial, especially in urban environments. This paper introduces a …
Fault Tolerance and Fallback Strategies in Connected and Automated Vehicles: A Review Open
Connected and Automated Vehicles (CAVs) are considered the future of transportation, offering increased safety, efficiency, and convenience. However, their reliance on sophisticated sensors and complex algorithms poses challenges, especial…
Driver Take-Over Behaviour Study Based on Gaze Focalization and Vehicle Data in CARLA Simulator Open
Autonomous vehicles are the near future of the automobile industry. However, until they reach Level 5, humans and cars will share this intermediate future. Therefore, studying the transition between autonomous and manual modes is a fascina…
Reinforcement Learning-Based Autonomous Driving at Intersections in CARLA Simulator Open
Intersections are considered one of the most complex scenarios in a self-driving framework due to the uncertainty in the behaviors of surrounding vehicles and the different types of scenarios that can be found. To deal with this problem, w…
$$360^{\circ }$$ real-time and power-efficient 3D DAMOT for autonomous driving applications Open
Autonomous Driving (AD) promises an efficient, comfortable and safe driving experience. Nevertheless, fatalities involving vehicles equipped with Automated Driving Systems (ADSs) are on the rise, especially those related to the perception …
Train here, drive there: ROS based end-to-end autonomous-driving pipeline validation in CARLA simulator using the NHTSA typology Open
Urban complex scenarios are the most challenging situations in the field of Autonomous Driving (AD). In that sense, an AD pipeline should be tested in countless environments and scenarios, escalating the cost and development time exponenti…
Gaze Focalization System for Driving Applications Using OpenFace 2.0 Toolkit with NARMAX Algorithm in Accidental Scenarios Open
Monitoring driver attention using the gaze estimation is a typical approach used on road scenes. This indicator is of great importance for safe driving, specially on Level 3 and Level 4 automation systems, where the take over request contr…
Drive-By-Wire Development Process Based on ROS for an Autonomous Electric Vehicle Open
This paper presents the development process of a robust and ROS-based Drive-By-Wire system designed for an autonomous electric vehicle from scratch over an open source chassis. A revision of the vehicle characteristics and the different mo…