In recent years, as intelligent transportation systems (ITS) such as autonomous driving and
advanced driver-assistance systems have become more popular, there has been a rise in …

Road pavement type classification is important in route planning, road maintenance and for
autonomous vehicles. In this paper, we propose a deep learning based method for …

Traditional image recognition technology currently cannot achieve the fast real-time high-
accuracy performance necessary for road recognition in intelligent driving. Deep learning …

The demand for several sources of situational data from the traffic environment has
intensified in recent years, through the development of applications in intelligent transport …

The types of road surfaces on which intelligent connected cars operate are complicated and
varied, and current research lacks the achievement of real-time and reasonably high …

Vision-based techniques for intelligent vehicles in heterogeneous road environments are
gaining significant attention from researchers and industrialists. Unfortunately, the …

Deep learning is a fast-growing field of research, in particular, for autonomous application. In
this study, a deep learning network based on various sensor data is proposed for identifying …

In order to classify road surface for intelligent vehicles, we develop a data set including day
and night driving from different cities. Meanwhile, the dataset contains various scenarios …

The demand for a variety of situational data from the traffic environment and its participants
has intensified with the development of applications in Intelligent Transport Systems (ITS) …

Accurate vehicle type classification serves a significant role in the intelligent transportation
system. It is critical for ruler to understand the road conditions and usually contributive for the …