In current years, the improvement of deep learning has brought about tremendous changes:
As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) …

Since the beginning of the 21st century, artificial intelligence (AI) has been resha** almost
all areas of human society, which has high potential to spark the fourth industrial revolution …

Despite significant progress in autonomous vehicles (AVs), the development of driving
policies that ensure both the safety of AVs and traffic flow efficiency has not yet been fully …

In the realm of autonomous vehicular systems, there has been a notable increase in end-to-
end algorithms designed for complete self-navigation. Researchers are increasingly …

Abstract Model-based reinforcement learning (RL) is anticipated to exhibit higher sample
efficiency than model-free RL by utilizing a virtual environment model. However, obtaining …

The infrastructure for vehicle-to-everything has facilitated the development of intelligent eco-
driving and energy management, exploring the energy-saving potential of connected hybrid …

With the growing prevalence of autonomous vehicles and the integration of intelligent and
connected technologies, the demand for effective and reliable vehicle speed control …

Trajectory prediction for heterogeneous traffic agents plays a crucial role in ensuring the
safety and efficiency of automated driving in highly interactive traffic environments …

In intelligent transportation systems, one key challenge for managing ride-hailing services is
the balancing of traffic supply and demand while meeting passenger needs within vehicle …

Model Predictive Path Integral (MPPI) is a recognized sampling-based approach for finite
horizon optimal control problems. However, the efficacy and computational efficiency of …