Experts confirm that 85% of the world's population is expected to live in cities by 2050.
Therefore, cities should be prepared to satisfy the needs of their citizens and provide the …

In this paper the various driving style analysis solutions are investigated. An in-depth
investigation is performed to identify the relevant machine learning and artificial intelligence …

Detecting traffic accidents as rapidly as possible is essential for traffic safety. In this study, we
use eXtreme Gradient Boosting (XGBoost)—a Machine Learning (ML) technique—to detect …

This paper summarizes the state of the art in connected vehicles-from the need for vehicle
data and applications thereof, to enabling technologies, challenges, and identified …

Internet of Things-enabled Intelligent Transportation Systems (ITS) are gaining significant
attention in academic literature and industry, and are seen as a solution to enhancing road …

We propose a packet switched platform for single chip systems which scales well to an
arbitrary number of processor like resources. The platform, which we call Network-on-Chip …

Cooperative Intelligent Transportation Systems, mainly represented by vehicular ad hoc
networks (VANETs), are among the key components contributing to the Smart City and …

Just as it has irrevocably reshaped social life, the fast growth of smartphone ownership is
now beginning to revolutionize the driving experience and change how we think about …

Road crashes are a growing concern of governments and are rising to become one of the
leading preventable causes of death, especially in develo** countries. The ubiquitous …

Human driving behaviors are personalized and unique, and the automobile fingerprint of
drivers could be helpful to automatically identify different driving behaviors and further be …