Guodong Du

Orcid: 0000-0001-7011-268X

Affiliations:
  • ETH Zurich, Institute of Dynamic System and Control, Zürich, Switzerland
  • Beijing Collaborative and Innovative Center for Electric Vehicle, Beijing, China (former)


According to our database1, Guodong Du authored at least 10 papers between 2020 and 2025.

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

Timeline

Legend:

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Bibliography

2025
Dependency-Aware Task Offloading Strategy via Heterogeneous Graph Neural Network and Deep Reinforcement Learning.
IEEE Internet Things J., July, 2025

Hierarchical Path Planning and Motion Control Framework Using Adaptive Scale Based Bidirectional Search and Heuristic Learning Based Predictive Control.
IEEE Trans. Veh. Technol., June, 2025

Improved Deep Reinforcement Learning for Efficient Motion Control of Autonomous Vehicle With Domain-Centralized Electronic and Electrical Architecture.
IEEE Internet Things J., June, 2025

Enhancing the Collaborative Decision-Making Performance of Connected and Autonomous Vehicles: A Multi-Modal Failure-Aware Graph Representation Approach.
IEEE Trans. Intell. Transp. Syst., May, 2025

2024
Efficient Motion Control for Heterogeneous Autonomous Vehicle Platoon Using Multilayer Predictive Control Framework.
IEEE Internet Things J., December, 2024

Joint Routing and Scheduling Optimization of In-Vehicle Time-Sensitive Networks Based on Improved Grey Wolf Optimizer.
IEEE Internet Things J., February, 2024

Graph Attention Network-Based Deep Reinforcement Learning Scheduling Framework for in-Vehicle Time-Sensitive Networking.
IEEE Trans. Ind. Informatics, 2024

Motion Control of Autonomous Vehicle with Domain-Centralized Electronic and Electrical Architecture based on Predictive Reinforcement Learning Control Method.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

2023
Hierarchical Motion Planning and Tracking for Autonomous Vehicles Using Global Heuristic Based Potential Field and Reinforcement Learning Based Predictive Control.
IEEE Trans. Intell. Transp. Syst., August, 2023

2020
Predictive Eco-Driving Application Considering Real-World Traffic Flow.
IEEE Access, 2020


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