Thanks to the rapid development of computer vision and deep learning technologies,
advanced driver assistance systems (ADAS) have recently become widespread. These …

Traffic congestion is becoming the issues of the entire globe. This study aims to explore and
review the data mining and machine learning technologies adopted in research and industry …

Cameras are the primary sensor in automated driving systems. They provide high
information density and are optimal for detecting road infrastructure cues laid out for human …

Advanced driver-assistance systems (ADASs) are safety features in automobiles. They
prevent crashes by changing the vehicle speed and maintaining a safe outdistance from the …

As a non-invasive method, vision-based driver monitoring aims to identify risky maneuvers
for intelligent vehicles and it has gained an increasing interest over recent years. However …

Neuromorphic vision sensors such as the Dynamic and Active-pixel Vision Sensor (DAVIS)
using silicon retina are inspired by biological vision, they generate streams of asynchronous …

Unmanned robots are increasingly used around humans in factories, malls, and hotels. As
they navigate our space, it is important to ensure that such robots do not collide with people …

Due to the growing awareness of driving safety and the development of sophisticated
technologies, advanced driving/driver assistance system (ADAS) has been equipped in …

This study proposes an applicable driver identification method using machine learning
algorithms with driving information. The driving data are collected by a 3‐axis …

Reducing traffic fatal crashes has been an important mission of transportation. With the rapid
development of sensor and Artificial Intelligence (AI) technologies, the computer vision (CV) …