Review and perspectives on driver digital twin and its enabling technologies for intelligent vehicles
Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving
and transportation systems to digitize and synergize connected automated vehicles …
and transportation systems to digitize and synergize connected automated vehicles …
Toward human-vehicle collaboration: Review and perspectives on human-centered collaborative automated driving
The last decade witnessed a great development of automated driving vehicles (ADVs) and
vehicle intelligence. The significant increment of machine intelligence poses a new …
vehicle intelligence. The significant increment of machine intelligence poses a new …
Milestones in autonomous driving and intelligent vehicles—part 1: Control, computing system design, communication, hd map, testing, and human behaviors
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace
due to the convenience, safety, and economic benefits. Although a number of surveys have …
due to the convenience, safety, and economic benefits. Although a number of surveys have …
An ensemble deep learning approach for driver lane change intention inference
With the rapid development of intelligent vehicles, drivers are increasingly likely to share
their control authorities with the intelligent control unit. For building an efficient Advanced …
their control authorities with the intelligent control unit. For building an efficient Advanced …
Personalized vehicle trajectory prediction based on joint time-series modeling for connected vehicles
Motion prediction for the leading vehicle is a critical task for connected autonomous
vehicles. It provides a method to model the leading-following vehicle behavior and analysis …
vehicles. It provides a method to model the leading-following vehicle behavior and analysis …
[HTML][HTML] Trajectory data-based traffic flow studies: A revisit
In this paper, we review trajectory data-based traffic flow studies that have been conducted
over the last 15 years. Our purpose is to provide a roadmap for readers who have an interest …
over the last 15 years. Our purpose is to provide a roadmap for readers who have an interest …
An interacting multiple model for trajectory prediction of intelligent vehicles in typical road traffic scenario
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 …
term trajectory prediction of an intelligent vehicle. This model is based on vehicle's physics …
Multi-step reinforcement learning for model-free predictive energy management of an electrified off-highway vehicle
The energy management system of an electrified vehicle is one of the most important
supervisory control systems which manages the use of on-board energy resources. This …
supervisory control systems which manages the use of on-board energy resources. This …
Convolutional neural network-based lane-change strategy via motion image representation for automated and connected vehicles
The lane-change decision-making module of automated and connected vehicles (ACVs) is
one of the most crucial and challenging issues to be addressed. Motivated by human beings' …
one of the most crucial and challenging issues to be addressed. Motivated by human beings' …
An intelligent lane-changing behavior prediction and decision-making strategy for an autonomous vehicle
W Wang, T Qie, C Yang, W Liu… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
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 …
surrounding vehicles is a significant factor affecting the driving safety. It is necessary to …