Xin Gao

Orcid: 0000-0002-7317-8059

Affiliations:
  • Beijing Institute of Technology, School of Mechanical Engineering, Beijing, China
  • Peking University, Institute for AI, Center for AI Safety and Governance, Beijing, China


According to our database1, Xin Gao authored at least 9 papers between 2022 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
Spatiotemporal Coordinated Decision-Making in Heterogeneous Platooning via Interflow Hub-and-Spoke Graph Reinforcement Learning.
IEEE Internet Things J., October, 2025

2024
Ethical Alignment Decision Making for Connected Autonomous Vehicle in Traffic Dilemmas via Reinforcement Learning From Human Feedback.
IEEE Internet Things J., December, 2024

Rate GQN: A Deviations-Reduced Decision-Making Strategy for Connected and Automated Vehicles in Mixed Autonomy.
IEEE Trans. Intell. Transp. Syst., January, 2024

SIF-STGDAN: A Social Interaction Force Spatial-Temporal Graph Dynamic Attention Network for Decision-Making of Connected and Autonomous Vehicles.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

2023
Graph Reinforcement Learning-Based Decision-Making Technology for Connected and Autonomous Vehicles: Framework, Review, and Future Trends.
Sensors, October, 2023

A Human Feedback-Driven Decision-Making Method Based on Multi-Modal Deep Reinforcement Learning in Ethical Dilemma Traffic Scenarios.
Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems, 2023

2022
Generalized Single-Vehicle-Based Graph Reinforcement Learning for Decision-Making in Autonomous Driving.
Sensors, 2022

Multi-Agent Decision-Making Modes in Uncertain Interactive Traffic Scenarios via Graph Convolution-Based Deep Reinforcement Learning.
Sensors, 2022

Graph Reinforcement Learning Application to Co-operative Decision-Making in Mixed Autonomy Traffic: Framework, Survey, and Challenges.
CoRR, 2022


  Loading...