Meaningful Human Control over Automated Driving Systems

Data-driven Semi-supervised Machine Learning with Surrogate Safety Measures for Abnormal Driving Behavior Detection

Detecting abnormal driving behavior is critical for road traffic safety and the evaluation of drivers' behavior. With the advancement of machine learning (ML) algorithms and the accumulation of naturalistic driving data, many ML models have been adopted for abnormal driving behavior detection. Most existing ML-based detectors rely on (fully)...

Connected Traffic of Vulnerable Bicyclists and Automated Vehicles: Deep Learning Trajectory Generation for Realistic Simulated Bicycle Intersection Crossings