Publications
Bootstrapped Neural Models for Predicting Self-Driving Vehicle Collisions With Quantified Confidence: Offline and Online Applications
Accidents in ADScene: a specific survey on AD L2+ functions
Scenario-based assesment of automated driving systems: How (not) to parameretize scenarios?
Coverage Metrics for a Scenario Database for the Scenario-Based Assesment of Automated Driving Systems
Test and validation of perception-based ADAS: modern solutions to traditional challenges
Workspace Envelope Manipulation for Stewart Platform Simulators with Redundant Degrees of Freedom
Open-Source Tool Based Framework for Automated Performance Evaluation of an AD Function
Formulating a dissimilarity metric for comparison of driving scenarios for Automated Driving Systems
WayWise: A rapid prototyping library for connected, autonomous vehicles
Bootstrapping Aggregation of Neural Models for Prediction of Intelligent Vehicle Performance with Quantified Uncertainty: Safety Assessment, Failure Analysis, and Online Speed Recommendations
Automated Vehicle Testing & Data Collection Efforts
https://doi.org/10.1007/978-3-031-34757-3