Autonomous driving (AD), including single-vehicle intelligent AD and vehicle–infrastructure
cooperative AD, has become a current research hot spot in academia and industry, and …

The rapid development of Autonomous Vehicles (AVs) increases the requirement for the
accurate prediction of objects in the vicinity to guarantee safer journeys. For effectively …

The technique of turning infrared (IR) radiation (heat) into visual images is known as thermal
infrared. Semantic segmentation aims to divide an input image based on information that is …

Autonomous driving has rapidly developed and shown promising performance with recent
advances in hardware and deep learning methods. High-quality datasets are fundamental …

Autonomous driving has rapidly developed and shown promising performance due to recent
advances in hardware and deep learning techniques. High-quality datasets are fundamental …

Multi-modal fusion is a basic task of autonomous driving system perception, which has
attracted many scholars' attention in recent years. The current multi-modal fusion methods …

Self evolution refers to the ability of a system to evolve autonomously towards a better
performance, which is a potential trend for autonomous driving systems based on self …

Driving behavior classification is an important direction in the field of social transportation
systems and advanced driving assistance system (ADAS), which has attracted more and …

Lane detection plays an important role in the field of automatic driving. Conventional
convolutional operations typically focus on local block-like region, while lane often span …

Nowadays, more than in the past, research is focused on the study and development of
enabling technologies to achieve the goal of autonomous navigation. The investigations …