This paper explores deep learning (DL) methods that are used or have the potential to be
used for traffic video analysis, emphasising driving safety for both autonomous vehicles and …

The essential requirement for precise localization of a self-driving car is a lane-level map
which includes road markings (RMs). Obviously, we can build the lane-level map by running …

Driving safety analysis has recently experienced unprecedented improvements thanks to
technological advances in precise positioning sensors, artificial intelligence (AI)-based …

Compared to 2D lanes, real 3D lane data is difficult to collect accurately. In this paper, we
propose a novel method for training 3D lanes with only 2D lane labels, called weakly …

The foundational role of datasets in defining the capabilities of deep learning models has
led to their rapid proliferation. At the same time, published research focusing on the process …

Autonomous driving research is an emerging area in the machine learning domain. Most
existing methods perform single-task learning, while multi-task learning (MTL) is more …

The active safety systems used in automotive field are largely exploiting lane detection
technique for warning the vehicle drivers to correct any unintended road departure and to …

AI-For-Mobility (AFM) is the new research platform to investigate and implement novel
control methods based on Artificial Intelligence (AI) within the Department of Vehicle System …

Recent years have witnessed the rapid advancements and commercial success of
autonomous vehicles due to the developments in Image Processing, Machine Learning and …

Lane detection under extreme conditions presents a highly challenging task that requires
capturing each crucial pixel to predict the complex topology of lane lines and differentiate …