104 citations · 325 across the 28 of their papers we have counts for
16 papers · 1 filter
The Era of End-to-End Autonomy: Transitioning from Rule-Based Driving to Large Driving Models
Eduardo Nebot, Julie Stephany Berrio Perez
Autonomous driving is undergoing a shift from modular rule based pipelines toward end to end (E2E) learning systems. This paper examines this transition by tracing the evolution fr…
Critical concrete scenario generation using scenario-based falsification
Dhanoop Karunakaran, Julie Stephany Berrio, Stewart Worrall +1
Autonomous vehicles have the potential to lower the accident rate when compared to human driving. Moreover, it is the driving force of the automated vehicles' rapid development ove…
Parameterisation of lane-change scenarios from real-world data
Dhanoop Karunakaran, Julie Stephany Berrio, Stewart Worrall +1
Recent Autonomous Vehicles (AV) technology includes machine learning and probabilistic techniques that add significant complexity to the traditional verification and validation met…
A Novel Probabilistic V2X Data Fusion Framework for Cooperative Perception
Mao Shan, Karan Narula, Stewart Worrall +4
The paper addresses the vehicle-to-X (V2X) data fusion for cooperative or collective perception (CP). This emerging and promising intelligent transportation systems (ITS) technolog…
Automatic lane change scenario extraction and generation of scenarios in OpenX format from real-world data
Dhanoop Karunakaran, Julie Stephany Berrio, Stewart Worrall +1
Autonomous Vehicles (AV)'s wide-scale deployment appears imminent despite many safety challenges yet to be resolved. The modern autonomous vehicles will undoubtedly include machine…
A Persistent and Context-aware Behavior Tree Framework for Multi Sensor Localization in Autonomous Driving
Siqi Yi, Stewart Worrall, Eduardo Nebot
Robust and persistent localisation is essential for ensuring the safe operation of autonomous vehicles. When operating in large and diverse urban driving environments, autonomous v…