activity
20242026
collaborators

8 papers

cs.RO2026

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…

cs.HC2025

Understanding Visually Impaired Tramway Passengers Interaction with Public Transport Systems

Dominik Mimra, Dominik Kaar, Enrico Del Re +4

Designing inclusive public transport services is crucial to developing modern, barrier-free smart city infrastructure. This research contributes to the design of inclusive public t…

cs.RO2025

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…

cs.HC2025

V2P Collision Warnings for Distracted Pedestrians: A Comparative Study with Traditional Auditory Alerts

Novel Certad, Enrico Del Re, Joshua Varughese +1

This study assesses a Vehicle-to-Pedestrian (V2P) collision warning system compared to conventional vehicle-issued auditory alerts in a real-world scenario simulating a vehicle on…

cs.RO2025

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…

cs.RO2025

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…