A comprehensive literature review reveals that there exist lots of ambiguities, confusion and
even contradictions in setting a car-following calibration problem. In particular, confusion …

Road crashes cost over a million lives each year. Consequently, researchers and transport
engineers continue their efforts to improve road safety and minimize road crashes. With the …

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 …

Trajectory clustering, which aims at discovering groups of similar trajectories, has long been
considered as a corner stone task for revealing movement patterns as well as facilitating …

An increase in the size of data repositories of spatiotemporal data has opened up new
challenges in the fields of spatiotemporal data analysis and data mining. Foremost among …

As the market penetration rate of automated vehicles (AVs) increases, there will be a
transition period when the traffic stream is composed of both AVs and human-driven …

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 …

Automated vehicles are expected to navigate complex urban environments safely along with
several non-cooperating agents. Therefore, accurate trajectory prediction is crucial for safe …

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 …

Vehicle fuel economy is greatly influenced by the driver's driving style. To achieve
remarkable promotion in the fuel economy, a novel predictive energy management strategy …