Driving prediction techniques (DPTs) are used to forecast the distributions of various future
driving conditions (FDC), like velocity, acceleration, driver behaviors etc. and the quality of …

Abstract Generalized Linear Models (GLMs) and XGBoost are widely used in insurance risk
pricing and claims prediction, with GLMs dominant in the insurance industry. The increasing …

Supervised learning approaches are widely used for driving style classification; however,
they often require a large amount of labeled training data, which is usually scarce in a real …

In light of increasing demands on decarbonized transportation systems, it became
increasingly necessary to meet performance and environmental requirements for …

Driving style analysis plays a pivotal role in intelligent vehicle design. This paper presents a
novel framework for driving style analysis based on primitive driving patterns. To this end, a …

Rear‐end collision crash is one of the most common accidents on the road. Accurate driving
style recognition considering rear‐end collision risk is crucial to design useful driver …

Misunderstanding of driver correction behaviors is the primary reason for false warnings of
lane-departure-prediction systems. We proposed a learning-based approach to predict …

With the vehicle to infrastructure and vehicle to vehicle communication information, it is
beneficial to improve the fuel economy of hybrid electric vehicle by providing the driver with …

The present study proposes a decision-making model based on different models of driver
behavior, aiming to ensure integration between road safety and crash reduction based on …

Accurately predicting and inferring a driver's decision to brake is critical for designing
warning systems and avoiding collisions. In this paper, we focus on predicting a driver's …