Autonomous driving is expected to provide a range of far-reaching economic, environmental
and safety benefits. In this study, we propose a fog computing based framework to assist …

The automotive industry is increasingly focusing on autonomous vehicles, leading to a need
for intelligent systems that enable safe and efficient self-driving. Fog computing is a …

The seven papers in this special section focuses on fog computing for autonomous and
connected automobiles. With advances in wireless communications, machine learning, and …

We are witnessing the evolution from Internet of Things (IoT) to Internet of Vehicles (IoV).
Internet connected vehicles can sense, communicate, analyze and make decisions. Rich …

Vehicle-based visual crowdsourcing is an emerging paradigm where the visual data
collected from dash cameras are analyzed with the aim of measuring phenomena of …

Fog computing consists of modest capability fog nodes located close to the data generation
sources. These nodes are ideal for executing small interactive tasks with a low latency …

Recent advances in fog computing had significantly impacted the development of the
Internet of Vehicles (IoV). Rapidly growing on-vehicle applications demand low-latency …

The Internet of Vehicles (IoV) is a decentralized network that enables data sharing between
connected vehicles and vehicular ad hoc networks (VANETs). However, since different IoV …

Emerging vehicular applications, such as real-time situational awareness and cooperative
lane change, demand for sufficient computing resources at the edge to conduct time-critical …

Intelligent transportation system (ITS) helps to improve traffic efficiency and ensure traffic
safety. The core of this system is the collection and analysis of sensor data and vehicle …