The last decade witnessed a great development of automated driving vehicles (ADVs) and
vehicle intelligence. The significant increment of machine intelligence poses a new …

Human drivers have different driving styles, experiences, and emotions due to unique
driving characteristics, exhibiting their own driving behaviors and habits. Various research …

In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …

The development of safety-oriented research and applications requires fine-grain vehicle
trajectories that not only have high accuracy, but also capture substantial safety-critical …

Considering that human-driven vehicles and autonomous vehicles (AVs) will coexist on
roads in the future for a long time, how to merge AVs into human drivers' traffic ecology and …

Driving behavior modeling is of great importance for designing safe, smart, and
personalized autonomous driving systems. In this paper, an internal reward function-based …

Vehicular Edge Computing (VEC) is the transportation version of Mobile Edge Computing
(MEC) in road scenarios. One key technology of VEC is task offloading, which allows …

In the future complex intelligent transportation environments, lane-changing behavior of
surrounding vehicles is a significant factor affecting the driving safety. It is necessary to …

Financial time series prediction is a hot topic in machine learning field, but existing works
barely catch the point of such data. In this study, we employ the most suitable preprocessing …

This article presents an interacting multiple model (IMM) for short-term prediction and long-
term trajectory prediction of an intelligent vehicle. This model is based on vehicle's physics …