5 papers · 1 filter
Assessing Localization Technologies for Pedestrian Collision Avoidance
Joshua Varughese, Joseba Gorospe, Novel Certad +1
Robust pedestrian safety is crucial to the next-generation of intelligent transportation systems. Such systems rely on active pedestrian localization and predictive collision alert…
Evaluating Pedestrian Risks in Shared Spaces Through Autonomous Vehicle Experiments on a Fixed Track
Enrico Del Re, Novel Certad, Joshua Varughese +1
The majority of research on safety in autonomous vehicles has been conducted in structured and controlled environments. However, there is a scarcity of research on safety in unregu…
Interaction of Autonomous and Manually Controlled Vehicles Multiscenario Vehicle Interaction Dataset
Novel Certad, Enrico del Re, Helena Korndörfer +6
The acquisition and analysis of high-quality sensor data constitute an essential requirement in shaping the development of fully autonomous driving systems. This process is indispe…
Extraction of Road Users' Behavior From Realistic Data According to Assumptions in Safety-Related Models for Automated Driving Systems
Novel Certad, Sebastian Tschernuth, Cristina Olaverri-Monreal
In this work, we utilized the methodology outlined in the IEEE Standard 2846-2022 for "Assumptions in Safety-Related Models for Automated Driving Systems" to extract information on…
Road Markings Segmentation from LIDAR Point Clouds using Reflectivity Information
Novel Certad, Walter Morales-Alvarez, Cristina Olaverri-Monreal
Lane detection algorithms are crucial for the development of autonomous vehicles technologies. The more extended approach is to use cameras as sensors. However, LIDAR sensors can c…