Develo** autonomous driving technologies necessitates addressing safety and cost
concerns. Both academic research and commercial applications of autonomous driving …

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

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

Driving safety is a top priority for autonomous vehicles. Orthogonal to prior work handling
accident-prone traffic events by algorithm designs at the policy level, we investigate a …

In the contemporary landscape, the escalating deployment of drones across diverse
industries has ushered in a consequential concern, including ensuring the security of drone …

Autonomous vehicles have the potential to revolutionize intelligent transportation by
improving traffic safety, increasing energy efficiency, and reducing congestion. In this study …

Recent years have witnessed a dramatic evolution in small-scale remote sensors such as
Unmanned aerial vehicles (UAVs). Characteristics such as automatic flight control, flight …

Reinforcement learning has emerged as an important approach for autonomous driving. A
reward function is used in reinforcement learning to establish the learned skill objectives …

As artificial intelligence (AI) has already seen numerous successful applications, the
upcoming challenge lies in how to realize artificial general intelligence (AGI). Self-learning …