Unmanned aerial vehicle (UAV) usage is increasing drastically worldwide as UAVs are used
in various industries for many applications, such as inspection, logistics, agriculture, and …

Autonomous driving (AD) holds the potential to revolutionize transportation efficiency, but its
success hinges on robust behavior planning (BP) mechanisms. Reinforcement learning (RL) …

In this article, a motion planning for autonomous driving on highway is studied. A high-level
motion planning controller with discrete action space is designed based on deep Q network …

Left turning for autonomous vehicles at intersections is challenging due to the various
driving behaviors from different human drivers and the strong interaction between the …

Safe driving decision-making is particularly important for automated commercial vehicles
(ACVs). Small passenger vehicles pay more attention to collision prevention, while …

Decision-making for automatic vehicles at unsignalized intersections with dense traffic is
one of the most challenging tasks. Due to the complex structure and frequent traffic …

As an increasing number of intelligent decision-making problems of vehicles are addressed
using implementations of deep learning (DL) methods, the interpretability of intelligent …

The current emergency vehicle priority control methods in road traffic net-works are difficult
to cope with the increasing traffic demand. Therefore, a traffic control method based on multi …

The control of a wing-in-ground craft (WIG) usually allows for many needs, like cruising,
speed, survival and stealth. Various degrees of emphasis on these requirements result in …

This study examines the impact of alcohol concentration on the precision of unmanned
aerial vehicle (UAV) operations. While the impact of alcohol impairment on various activities …