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 …

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 …

Today's smartphones and mobile devices typically embed advanced motion sensors. Due to
their increasing market penetration, there is a potential for the development of distributed …

Driver behavior impacts traffic safety, fuel/energy consumption and gas emissions. Driver
behavior profiling tries to understand and positively impact driver behavior. Usually driver …

This paper highlights the role of humans in the next generation of driver assistance and
intelligent vehicles. Understanding, modeling, and predicting human agents are discussed …

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 …

Smartphone-based insurance telematics or usage based insurance is a disruptive
technology which relies on insurance premiums that reflect the risk profile of the driver; …

The present work investigates the use of smartphones as an alternative to gather data for
driving behavior analysis. The proposed approach incorporates i. a device reorientation …

Road accidents and vehicular emissions are two significant issues related to road
transportation, affecting both human life and the environment. Prior research suggests that …

We develop ensemble convolutional neural networks (CNNs) to classify the transportation
mode of trip data collected as part of a large-scale smartphone travel survey in Montreal …