Understanding drivers' behavioral characteristics is critical for the design of decision-making
modules in autonomous vehicles (AVs) and advanced driver assistance systems (ADASs) …

The accuracy of the data is crucial to the real-time prediction of autonomous driving. Due to
factors such as weather and the accuracy of data collection equipment, there frequently exist …

The prediction of lane‐change behavior is a challenging issue in intelligent and connected
vehicles (ICVs), which can help vehicles predict in advance and change lanes safely. In this …

Driving behavior recognition has attracted wide attention as it can act as an important
reference input of many vehicle intelligent control systems. In this paper, a real-time …

Lane change identification and lane change prediction are important tasks for the
Connected-Vehicle (CV) technologies. Since both connected vehicles and non-connected …

This paper presents a context-aware adaptive assembly assistance system meant to support
factory workers by embedding predictive capabilities. The research is focused on the …

Due to the ability to support a wide range of applications and to involve infrastructure
elements, connected and automated vehicles (CAVs) technology has played an important …

The maintenance paradigm has evolved over the last few years and companies that want to
remain competitive in the market need to provide condition-based maintenance (CBM). The …

Based on manifold learning (ML), a novel driver behavior recognition (DBR) method is
proposed in this paper to recognize the lane-changing behaviors of surrounding vehicles …

This paper proposes a novel MDP framework to deal with the accuracy of the motorcycle
driving model. It proposes a weighted and unweighted Dynamical-Discretized Reward Field …