6 papers
Practical validation of synthetic pre-crash scenarios
Jian Wu, Ulrich Sander, Carol Flannagan +1
The representativeness of synthetic pre-crash scenarios is crucial for assessing the safety impact of Driving Automation Systems through virtual simulations. However, a gap remains…
Practical Equivalence Testing and Its Application in Synthetic Pre-Crash Scenario Validation
Jian Wu, Ulrich Sander, Carol Flannagan +2
The use of representative pre-crash scenarios is critical for assessing the safety impact of driving automation systems through simulation. However, a gap remains in the robust eva…
Strategic decision points in experiments: A predictive Bayesian optional stopping method
Xiaomi Yang, Carol Flannagan, Jonas Bärgman
Sample size determination is crucial in experimental design, especially in traffic and transport research. Frequentist statistics require a fixed sample size determined by power an…
Evaluation of adaptive sampling methods in scenario generation for virtual safety impact assessment of pre-crash safety systems
Xiaomi Yang, Henrik Imberg, Carol Flannagan +1
Virtual safety assessment plays a vital role in evaluating the safety impact of pre-crash safety systems such as advanced driver assistance systems (ADAS) and automated driving sys…
RAVE Checklist: Recommendations for Overcoming Challenges in Retrospective Safety Studies of Automated Driving Systems
John M. Scanlon, Eric R. Teoh, David G. Kidd +12
The public, regulators, and domain experts alike seek to understand the effect of deployed SAE level 4 automated driving system (ADS) technologies on safety. The recent expansion o…
Model-based generation of representative rear-end crash scenarios across the full severity range using pre-crash data
Jian Wu, Carol Flannagan, Ulrich Sander +1
Generating representative rear-end crash scenarios is crucial for safety assessments of Advanced Driver Assistance Systems (ADAS) and Automated Driving systems (ADS). However, exis…