Zhiwen Chen
Research Assistant, SJTU UniAD Algo Intern, SenseTime B.Eng. Vehicle Engineering, Tongji
Hi! 👋 I'm Zhiwen Chen, currently a Research Assistant at Shanghai Jiao Tong University and an incoming Ph.D. student at the Hong Kong University of Science and Technology (starting January 2026). I received my B.Eng. 🎓 in Vehicle Engineering from Tongji University.
My research sits at the intersection of 🚗 Autonomous Driving, 🤖 Reinforcement Learning, and 🔮 Large Vision-Language Models. I focus on RL- and LLM-driven end-to-end driving and trajectory planning, aiming to build agentic driving systems that coordinate multiple planners and make human-like decisions in complex urban environments. 🏙️
Timeline
Incoming Ph.D. Student
Hong Kong University of Science and Technology
Research Assistant
Shanghai Jiao Tong University
Graduate Researcher, Vehicle Engineering
Tongji University
Algorithm Research Intern
SenseTime Research
Short-term Intern
SAIC Volkswagen
B.Eng. in Vehicle Engineering
Tongji University
Publications
IEEE TPAMI 2025
under review
Survey of General End-to-End Autonomous Driving: A Unified Perspective
CVPR 2026
under review
CityWeave: Weaving User Needs and World Constraints for Personalized and Reliable Travel Route Planning
A. Wang, Zhiwen Chen, S. Wang, Q. Xia, J. Li
NeurIPS 2025
accepted
HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving
Zhiwen Chen, H. Deng, Z. Li, H. Wen, G. Jin, R. Yu, B. Leng
Journal of Intelligent Transportation Systems
under review
Efficient and Flexible Autonomous Parking Planning based on Adaptive Multi-Step Motion Primitives
B. Leng, Zhiwen Chen, Z. Li, L. Xiong
IEEE Transactions on Neural Networks and Learning Systems
under review
A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspective
Z. Li, G. Jin, R. Yu, Zhiwen Chen, N. Li, W. Han, L. Xiong, B. Leng, J. Hu, I. Kolmanovsky, D. Filev
Journal of Tongji University (Natural Science Edition) 2022
accepted
A Global Path Planning Method for Multi-Vehicle Autonomous Parking Based on Multi-Attribute Decision Making
Zhiwen Chen, Z. Li, J. Wu, et al.
Experience
Research Assistant — Shanghai Jiao Tong University
Conducting research on automated driving motion planning methods at the Artificial Intelligence Institute. Focusing on utilizing reinforcement learning (RL) and world models instead of Mixture-of-Experts (MoE) techniques in LLMs.
Algorithm Research Intern — SenseTime Research
Built scenarios in the CARLA simulator to generate simulation data for the UniAD framework. Performed subsequent data processing and model training based on the generated simulation data.
Short-term Intern — SAIC Volkswagen
Gained an understanding of the EHH department's structure. Explored the applications and technical prospects of AI in intelligent driving.
Portfolio
Roadside-Information-Enhanced Interactive Learning for Decision-Making and Control
Joint project with Changan Automobile. Constructed risk constraints against unreasonable driving actions. Established a self-learning decision and control method guided by rule-based mechanisms and game theory.
Research on Planning and Control Algorithms for Collaborative Autonomous Parking
Optimized local parking paths and completed validation through real-world vehicle testing.
A Global Path Planning Platform for Multi-Vehicle Parking
Developed a global path planning platform for multi-vehicle parking. Implemented a complete end-to-end automatic parking system covering multi-vehicle space allocation, global guidance, local path planning, and demonstration on a visualization platform.
An Intelligent Sign Language Translation and Interaction System for the Hearing-Impaired
Joint project with Huawei. Achieved real-time recognition of sign language and conversion into text.