4 papers
Efficient Sequential Neural Network with Spatial-Temporal Attention and Linear LSTM for Robust Lane Detection Using Multi-Frame Images
Sandeep Patil, Yongqi Dong, Haneen Farah +1
Lane detection is a crucial perception task for all levels of automated vehicles (AVs) and Advanced Driver Assistance Systems, particularly in mixed-traffic environments where AVs…
Towards Developing Socially Compliant Automated Vehicles: Advances, Expert Insights, and A Conceptual Framework
Yongqi Dong, Bart van Arem, Haneen Farah
Automated Vehicles (AVs) hold promise for revolutionizing transportation by improving road safety, traffic efficiency, and overall mobility. Despite the steady advancement in high-…
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…
Understanding cyclists' perception of driverless vehicles through eye-tracking and interviews
Siri Hegna Berge, Joost de Winter, Dimitra Dodou +6
As automated vehicles (AVs) become increasingly popular, the question arises as to how cyclists will interact with such vehicles. This study investigated (1) whether cyclists spont…