Machine Learning (ML) has emerged as an attractive and viable technique to provide
effective solutions for a wide range of application domains. An important application domain …

Driver identification has been popular in the field of driving behavior analysis, which has a
broad range of applications in anti-thief, driving style recognition, insurance strategy, and …

Rapid advances in artificial intelligence (AI) and machine learning are creating products and
services with the potential not only to change the environment in which actuaries operate …

Due to the continued digitization of industrial and societal processes, including the
deployment of networked sensors, we are witnessing a rapid proliferation of time-ordered …

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 …

This paper deals with driver identification and fingerprinting and its application for enhanced
driver profiling and car security in connected cars. We introduce a new driver identification …

Modern vehicles are equipped with a myriad of sensors. Proprioceptive sensors monitor the
vehicle status and operation, whereas exteroceptive ones sense the external environment …

Driver profiling, which is the process of extracting driver preferences and behavioral patterns
from collected driving data, can be performed on a microscopic or macroscopic scale …

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

Mobile telematics is a relatively new innovation that involves collecting data on driving
behavior using the internal sensors in a smartphone rather than from an in-vehicle data …