5 citations · 9 across the 9 of their papers we have counts for
10 papers
Hamilton-Jacobi Reachability-Based Safe Reinforcement Learning for Emergency Collision Avoidance
Yuhong Jiang, Shiyue Zhao, Junzhi Zhang +4
Emergency collision avoidance under extreme driving conditions demands safety-critical control that accounts for both obstacle proximity and vehicle dynamic stability over a future…
CuraLight: Debate-Guided Data Curation for LLM-Centered Traffic Signal Control
Qing Guo, Xinhang Li, Junyu Chen +4
Traffic signal control (TSC) is a core component of intelligent transportation systems (ITS), aiming to reduce congestion, emissions, and travel time. Recent approaches based on re…
Kimi K2.5: Visual Agentic Intelligence
Kimi Team, Tongtong Bai, Yifan Bai +333
We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…
A Dual Large Language Models Architecture with Herald Guided Prompts for Parallel Fine Grained Traffic Signal Control
Qing Guo, Xinhang Li, Junyu Chen +4
Leveraging large language models (LLMs) in traffic signal control (TSC) improves optimization efficiency and interpretability compared to traditional reinforcement learning (RL) me…
Retrieval Augmented Generation-Enhanced Distributed LLM Agents for Generalizable Traffic Signal Control with Emergency Vehicles
Xinhang Li, Qing Guo, Junyu Chen +4
With increasing urban traffic complexity, Traffic Signal Control (TSC) is essential for optimizing traffic flow and improving road safety. Large Language Models (LLMs) emerge as pr…
Progression Cognition Reinforcement Learning with Prioritized Experience for Multi-Vehicle Pursuit
Xinhang Li, Yiying Yang, Zheng Yuan +6
Multi-vehicle pursuit (MVP) such as autonomous police vehicles pursuing suspects is important but very challenging due to its mission and safety critical nature. While multi-agent…
Graded-Q Reinforcement Learning with Information-Enhanced State Encoder for Hierarchical Collaborative Multi-Vehicle Pursuit
Yiying Yang, Xinhang Li, Zheng Yuan +3
The multi-vehicle pursuit (MVP), as a problem abstracted from various real-world scenarios, is becoming a hot research topic in Intelligent Transportation System (ITS). The combina…
An Opponent-Aware Reinforcement Learning Method for Team-to-Team Multi-Vehicle Pursuit via Maximizing Mutual Information Indicator
Qinwen Wang, Xinhang Li, Zheng Yuan +3
The pursuit-evasion game in Smart City brings a profound impact on the Multi-vehicle Pursuit (MVP) problem, when police cars cooperatively pursue suspected vehicles. Existing studi…
Confidence Estimation Transformer for Long-term Renewable Energy Forecasting in Reinforcement Learning-based Power Grid Dispatching
Xinhang Li, Zihao Li, Nan Yang +7
The expansion of renewable energy could help realizing the goals of peaking carbon dioxide emissions and carbon neutralization. Some existing grid dispatching methods integrating s…
A Credibility-aware Swarm-Federated Deep Learning Framework in Internet of Vehicles
Zhe Wang, Xinhang Li, Tianhao Wu +2
Federated Deep Learning (FDL) is helping to realize distributed machine learning in the Internet of Vehicles (IoV). However, FDL's global model needs multiple clients to upload lea…