Intelligent Automation (IA) in automobiles combines robotic process automation and artificial
intelligence, allowing digital transformation in autonomous vehicles. IA can completely …

The Internet of Vehicles (IoV) is an active area for innovation and an essential tool in
achieving smart cities through the integration of vehicles with the Internet of Things (IoT). IoV …

The development of new assessment methods for the performance of automated vehicles is
essential to enable the deployment of automated driving technologies, due to the complex …

Knowledge representation and reasoning has a long history of examining how knowledge
can be formalized, interpreted, and semantically analyzed by machines. In the area of …

Ontology is the explicit and formal representation of the concepts in a domain and relations
among them. Transportation science is a wide domain dealing with mobility over various …

Modern Artificial Intelligence (AI) methods can produce a large quantity of accurate and
richly described data, in domains such as surveillance or automation. As a result, the need …

Automated Driving (AD) datasets, when used in combination with deep learning techniques,
have enabled significant progress on difficult AD tasks such as perception, trajectory …

Trajectory prediction in traffic scenes involves accurately forecasting the behaviour of
surrounding vehicles. To achieve this objective it is crucial to consider contextual …

Autonomous vehicles perceive the environment with different kinds of sensors (camera,
radar, lidar...). They must evolve in an unpredictable environment and a wide context of …

Abstract Automated Vehicles (AVs) are designed and programmed to follow traffic rules.
However, there is no separate and comprehensive regulatory framework dedicated to AVs …