4 papers
Edge Case Detection in Automated Driving: Methods, Challenges, and Future Directions
Saeed Rahmani, Sabine Rieder, Erwin de Gelder +6
Automated vehicles (AVs) promise to enhance transportation safety and efficiency. However, ensuring their reliability in real-world conditions remains challenging, particularly due…
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…
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…
Designing a Robust and Cost-Efficient Electrified Bus Network with Sparse Energy Consumption Data
Sara Momen, Yousef Maknoon, Bart van Arem +1
This paper addresses the challenges of charging infrastructure design (CID) for electrified public transport networks using Battery Electric Buses (BEBs) under conditions of sparse…