11 citations · 26 across the 11 of their papers we have counts for
5 papers · 1 filter
Data-Driven Semi-Supervised Machine Learning with Safety Indicators for Abnormal Driving Behavior Detection
Yongqi Dong, Lanxin Zhang, Haneen Farah +2
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 ac…
Intelligent Anomaly Detection for Lane Rendering Using Transformer with Self-Supervised Pre-Training and Customized Fine-Tuning
Yongqi Dong, Xingmin Lu, Ruohan Li +3
The burgeoning navigation services using digital maps provide great convenience to drivers. Nevertheless, the presence of anomalies in lane rendering map images occasionally introd…
Mode substitution induced by electric mobility hubs: results from Amsterdam
Fanchao Liao, Jaap Vleugel, Gustav Bösehans +5
Electric mobility hubs (eHUBS) are locations where multiple shared electric modes including electric cars and e-bikes are available. To assess their potential to reduce private car…
Effect of eHMI on pedestrian road crossing behavior in shared space with Automated Vehicles-A Virtual Reality study
Yan Feng, Haneen Farah, Bart van Arem
A shared space area is a low-speed urban area in which pedestrians, cyclists, and vehicles share the road, often relying on informal interaction rules and greatly expanding freedom…
Safe, Efficient, Comfort, and Energy-saving Automated Driving through Roundabout Based on Deep Reinforcement Learning
Henan Yuan, Penghui Li, Bart van Arem +2
Traffic scenarios in roundabouts pose substantial complexity for automated driving. Manually mapping all possible scenarios into a state space is labor-intensive and challenging. D…