Shallow neural networks process the features directly, while deep networks extract features
automatically along with the training. Both models suffer from overfitting or poor …

Human factors are the primary catalyst for traffic accidents. Among different factors, fatigue,
distraction, drunkenness, and/or recklessness are the most common types of abnormal …

The advent of in-vehicle networking systems as well as state-of-the-art sensors and
communication technologies have facilitated the collection of large volume and almost real …

Driving style detection is an essential real-world requirement in diverse contexts, such as
traffic safety, car insurance and fuel consumption optimization. However, the existing …

Intelligent transportation systems, or ITS for short, includes a variety of services and
applications such as road traffic management, traveler information systems, public transit …

The propelling torque of a plug-in hybrid electric vehicle (PHEV) is provided by the engine
and driving motor. However, the driver style has a great influence on the fuel economy …

Driving style recognition provides an effective way to understand human driving behaviors
and thereby plays an important role in the automotive sector. However, most works fail to …

Risky driving behaviors can cause accidents, which may result in major material and moral
damages. Due to the increase in road accidents, it has become an important issue to identify …

Driving behaviour understanding is of vital importance in improving transportation safety and
promoting the development of Intelligent Transportation Systems (ITS). As a long-standing …

Driving behavior classification has received increasing attention in recent years, where
driving maneuver classification plays an important role. The first step of building a driving …