Zhuoren Li
Scholar

Zhuoren Li

Google Scholar ID: 5HSKGBUAAAAJ
Ph.D. Candidate
autonomous vehiclesintelligent transportationmotion planningreinforcement learning
Citations & Impact
All-time
Citations
186
 
H-index
6
 
i10-index
5
 
Publications
20
 
Co-authors
3
list available
Resume (English only)
Academic Achievements
  • Oct 2025: Paper on Multi-timescale Hierarchical RL accepted by IEEE Robot. Autom. Lett. (Q1, IF 5.3)
  • Sep 2025: Paper on LLM-enhanced RL accepted by NeurIPS 2025
  • Aug 2025: Paper on Convergent Harmonious RL for lane changing accepted by IEEE Trans. Intell. Transp. Syst. (Q1, IF 8.4)
  • Jun 2025: Paper on Multi-mode Evasion Assistance Control accepted by Chin. J. Mech. Eng. (Q1, IF 4.5)
  • Mar 2025: Paper on Safe RL for Lane Change Decision-Making accepted by Chin. J. Mech. Eng. (Q1, IF 4.5)
  • Oct 2024: Paper on Interaction-Aware RL won SAE International Outstanding Technical Paper Award at SAE ICVS 2024
  • Jul 2024: Paper on Hybrid Parameterized Action Space-based RL accepted by IEEE ITSC 2024
  • Oct 2023: Paper on POMDP-based Motion Planning accepted by IEEE Trans. Intell. Transp. Syst. (Q1, IF 8.4)
  • Jul 2023: Two papers on safe RL decision-making and Hybrid MPC-based motion planning accepted by IEEE ITSC 2023
  • Participated in 4 engineering projects, 7 government-funded projects, and authored/co-authored over 8 grant proposals as a key contributor
Research Experience
  • Sep 2022 – Present: Risk-Aware Safe RL for Autonomous Driving, enhancing safety via prior-knowledge-based constraints
  • Dec 2024 – Present: LLM-enhanced RL for Autonomous Driving, improving scenario understanding while mitigating hallucinations
  • Dec 2023 – Present: Control Granularity Research using skill primitives and parameterized action spaces for smooth driving
  • Sep 2021 – Jun 2023: Optimization-based Motion Planning for smooth, stable, and fast trajectory generation
  • Feb 2021 – Aug 2021: Parking Path Planning based on geometric curves and MPC optimization
  • Since 2021: Student Director of the Intelligent Decision Research Group at TJU-IIV, leading research on safe RL, interactive decision-making, and trajectory planning on unstructured roads