Recently, thanks to the introduction of human feedback, Chat Generative Pre-trained
Transformer (ChatGPT) has achieved remarkable success in the language processing field …

Decision-making and motion planning are extremely important in autonomous driving to
ensure safe driving in a real-world environment. This study proposes an online evolutionary …

In order to solve the manual labelling, long-tail effect and driving conservatism of the existing
decision-making algorithm. This paper proposed an integrated decision-making framework …

This paper proposed a deep reinforcement learning based reference speed planning
strategy to co-optimize the fuel economy, driving safety, and travel efficiency of connected …

Drivers are the center of vehicles and transportation systems. Because of the rapid
development of advanced technologies, artificial drivers have been developed as key …

Merge scenarios on highway are often challenging for autonomous driving, due to its lack of
sufficient tacit understanding on and subtle interaction with human drivers in the traffic flow …

One of the most challenging problems in human-machine co-work is the gap between
human intention and the machine's understanding and execution. Large Language Models …

An intelligent driving system should be capable of dynamically formulating appropriate
driving strategies based on the current environment and vehicle status, while ensuring the …

One of the main challenges faced by autonomous vehicles operating in mixed traffic
scenarios pertains to ensuring safe and efficient navigation, particularly adhering to the …

Automated driving (AD) aims at human-level intelligence and good cooperation with
humans. Therefore, it is necessary to consider the characteristics of human behavior and …