Shiyue Zhao
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View article: SafeDrive: Knowledge- and data-driven risk-sensitive decision-making for autonomous vehicles with Large Language Models
SafeDrive: Knowledge- and data-driven risk-sensitive decision-making for autonomous vehicles with Large Language Models Open
Recent advancements in autonomous vehicles (AVs) leverage Large Language Models (LLMs) to perform well in normal driving scenarios. However, ensuring safety in dynamic, high-risk environments and managing safety-critical long-tail events r…
View article: RiskNet: Interaction-Aware Risk Forecasting for Autonomous Driving in Long-Tail Scenarios
RiskNet: Interaction-Aware Risk Forecasting for Autonomous Driving in Long-Tail Scenarios Open
Ensuring the safety of autonomous vehicles (AVs) in long-tail scenarios remains a critical challenge, particularly under high uncertainty and complex multi-agent interactions. To address this, we propose RiskNet, an interaction-aware risk …
View article: Safety-Critical Human-Machine Shared Driving for Vehicle Collision Avoidance based on Hamilton-Jacobi reachability
Safety-Critical Human-Machine Shared Driving for Vehicle Collision Avoidance based on Hamilton-Jacobi reachability Open
Road safety continues to be a pressing global issue, with vehicle collisions imposing significant human, societal, and economic burdens. Human-machine shared collision avoidance in critical collision scenarios aims to aid drivers' accident…
View article: SafeDrive: Knowledge- and Data-Driven Risk-Sensitive Decision-Making for Autonomous Vehicles with Large Language Models
SafeDrive: Knowledge- and Data-Driven Risk-Sensitive Decision-Making for Autonomous Vehicles with Large Language Models Open
Recent advancements in autonomous vehicles (AVs) use Large Language Models (LLMs) to perform well in normal driving scenarios. However, ensuring safety in dynamic, high-risk environments and managing safety-critical long-tail events remain…
View article: High-Speed Cornering Control and Real-Vehicle Deployment for Autonomous Electric Vehicles
High-Speed Cornering Control and Real-Vehicle Deployment for Autonomous Electric Vehicles Open
Executing drift maneuvers during high-speed cornering presents significant challenges for autonomous vehicles, yet offers the potential to minimize turning time and enhance driving dynamics. While reinforcement learning (RL) has shown prom…
View article: Adaptive Decision-Making for Autonomous Vehicles: A Learning-Enhanced Game-Theoretic Approach in Interactive Environments
Adaptive Decision-Making for Autonomous Vehicles: A Learning-Enhanced Game-Theoretic Approach in Interactive Environments Open
This paper proposes an adaptive behavioral decision-making method for autonomous vehicles (AVs) focusing on complex merging scenarios. Leveraging principles from non-cooperative game theory, we develop a vehicle interaction behavior model …
View article: Vehicle Ride Comfort Control in the Post-Braking Phase Using Residual Reinforcement Learning
Vehicle Ride Comfort Control in the Post-Braking Phase Using Residual Reinforcement Learning Open