The incumbent Internet of Things suffers from poor scalability and elasticity exhibiting in
communication, computing, caching and control (4Cs) problems. The recent advances in …

This comprehensive review focuses on the Autonomous Driving System (ADS), which aims
to reduce human errors that are the reason for about 95% of car accidents. The ADS …

Automated vehicles (AVs) are widely considered to play a crucial role in future transportation
systems because of their speculated capabilities in improving road safety, saving energy …

Trajectory planning is essential for self-driving vehicles and has stringent requirements for
accuracy and efficiency. The existing trajectory planning methods have limitations in the …

Kinodynamic motion planning is critical for autonomous vehicles with high maneuverability
in dynamic environments. However, obtaining near-optimal motion planning solutions with …

The roundabout is a typical changeable, interactive scenario in which automated vehicles
should make adaptive and safe decisions. In this article, an optimization embedded …

This study proposes a novel eco-driving control strategy for connected and automated
hybrid electric vehicles, which utilizes deep reinforcement learning (DRL) to optimize …

This article proposes a motion planning approach for autonomous electric vehicles to
generate an appropriate planned path according to the time-varying surrounding …

Autonomous vehicle (AV) integration poses a significant challenge for intelligent
transportation systems (ITSs). The ability to automatically coordinate complex AV operations …

Collision risk modeling with multiple surrounding target vehicles (TVs) is essential for host
vehicle (HV) trajectory planning, especially considering challenging TV lateral behaviors …