Bo Hu

Orcid: 0000-0003-2995-2358

Affiliations:
  • Chongqing University of Technology, Chongqing, China


According to our database1, Bo Hu authored at least 12 papers between 2019 and 2026.

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

2026
MeUAL: Model-Enhanced Uncertainty-Aware Safe Reinforcement Learning for Safety-Critical Autonomous Highway Overtaking.
IEEE Trans. Intell. Transp. Syst., April, 2026

A vehicle lateral control algorithm that directly performs safe self-learning in real-world environments.
Eng. Appl. Artif. Intell., 2026

Transformer-based offline-to-online reinforcement learning for decision-making and control in autonomous driving.
Eng. Appl. Artif. Intell., 2026

2025
A Transformer Optimized Planner for Autonomous Vehicle On-Ramping Merging Task.
IEEE Trans. Ind. Electron., December, 2025

An uncertainty-aware safe-evolving reinforcement learning algorithm for decision-making and control in highway autonomous driving.
Eng. Appl. Artif. Intell., 2025

A knowledge-guided reinforcement learning method for lateral path tracking.
Eng. Appl. Artif. Intell., 2025

2024
A Data-Driven Reinforcement Learning Based Energy Management Strategy via Bridging Offline Initialization and Online Fine-Tuning for a Hybrid Electric Vehicle.
IEEE Trans. Ind. Electron., October, 2024

2023
A Data-Driven Solution for Energy Management Strategy of Hybrid Electric Vehicles Based on Uncertainty-Aware Model-Based Offline Reinforcement Learning.
IEEE Trans. Ind. Informatics, June, 2023

2022
A Deployment-Efficient Energy Management Strategy for Connected Hybrid Electric Vehicle Based on Offline Reinforcement Learning.
IEEE Trans. Ind. Electron., 2022

2021
Shifting Deep Reinforcement Learning Algorithm Toward Training Directly in Transient Real-World Environment: A Case Study in Powertrain Control.
IEEE Trans. Ind. Informatics, 2021

An Edge Computing Framework for Powertrain Control System Optimization of Intelligent and Connected Vehicles Based on Curiosity-Driven Deep Reinforcement Learning.
IEEE Trans. Ind. Electron., 2021

2019
Reinforcement Learning Approach to Design Practical Adaptive Control for a Small-Scale Intelligent Vehicle.
Symmetry, 2019


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