Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving
and transportation systems to digitize and synergize connected automated vehicles …

Construction machinery and robots are essential equipment for major infrastructure. The
application of deep learning technology can improve the construction quality and alleviate …

With the development of artificial intelligence technology, intelligent machines are
increasingly equipped with human-like abilities such as autonomous decision-making …

Advanced driver assistance systems (ADAS) aim to increase safety and reduce mental
workload. However, the gap in the understanding of the closed-loop driver–vehicle …

In this article, a human–machine adaptive shared control method is proposed for automated
vehicles (AVs) under automation performance degradation. First, a novel risk assessment …

General introduction of unconditionally and conditionally automated vehicles is expected to
have a highly positive impact on the society, from increased accessibility to mobility and …

The lane-keeping assistance design for steer-by-wire road vehicles is a multi-objective
control problem that addresses lane tracking, improvement of driver comfort and ensuring …

This paper proposes a novel deep learning framework for multi-modal motion prediction.
The framework consists of three parts: recurrent neural network to process target agent's …

Decision-making is critical for lane change in autonomous driving. Reinforcement learning
(RL) algorithms aim to identify the values of behaviors in various situations and thus they …

Emotion and a broader range of affective and cognitive states play an important role on the
road. While this has been predominantly investigated in terms of driver safety, the …