Multimodal remote sensing data classification can enhance a model's ability to distinguish
land features through multimodal data fusion. In this context, how to help models understand …

Abstract In Off-Policy reinforcement learning (RL), the experience imbalance problem can
affect learning performance. The experience imbalance problem refers to the phenomenon …

Reinforcement learning (RL) has been widely used in decision-making tasks, but it cannot
guarantee the agent's safety in the training process due to the requirements of interaction …

Green wave speed guidance is able to reduce the vehicle delay caused by unnecessary
starting and braking at signalized intersections and ease traffic congestion, especially with …

The application of autonomous driving system (ADS) technology can significantly reduce
potential accidents involving vulnerable road users (VRUs) due to driver error. This paper …

Safety has been a key goal for autonomous driving since its inception, and we believe
recognizing and responding to risk is a key component of safety. In this work, we aim to …

Lane-changing decisions, which are crucial for autonomous vehicle path planning, face
practical challenges due to rule-based constraints and limited data. Deep reinforcement …

Autonomous vehicles mitigate road accidents and provide safe transportation with a smooth
traffic flow. They are expected to greatly improve the quality of the elderly or people with …

Humanlike driving is significant in improving the safety and comfort of automated vehicles.
This paper proposes a personalized motion planning method with driver characteristics in …

Reinforcement learning (RL) and imitation learning (IL) are quite two useful machine
learning techniques that were shown to be potential in enhancing navigation performance …