Safe, Efficient, Comfort, and Energy-saving Automated Driving through Roundabout Based on Deep Reinforcement Learning

Traffic scenarios in roundabouts pose substantial complexity for automated driving. Manually mapping all possible scenarios into a state space is labor-intensive and challenging. Deep reinforcement learning (DRL) with its ability to learn from interacting with the environment emerges as a promising solution for training such automated driving...

Investigation on Transient Failure Mode of Asymmetric Trench Gate SiC MOSFET Under Single-Pulse Avalanche Stress

In this article, the avalanche withstand capability and transient failure model of commercial 1200 V asymmetric trench gate SiC MOSFETs are investigated by experiment and simulation under single-pulse unclamped inductive switching (UIS) conditions. The limiting avalanche current and limiting avalanche energy of the device are determined by...

Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Interactive Traffic Scenarios

A reliable multi-agent decision-making system is highly demanded for safe and efficient operations of connected and autonomous vehicles (CAVs). In order to represent the mutual effects between vehicles and model the dynamic traffic environments, this research proposes an integrated and open-source framework to realize different Graph...