From the 1 of 5 linked papers with an AI index.
5 papers
DRIFT: Drift and Aggregation for Motion Planning
Yining Xing, Zhiyuan Liu, Zehong Ke +2
The paper introduces DRIFT, a real‑time motion planner that creates multiple trajectory proposals in a compact latent space and directly aggregates them into a single executable pa…
CLEAR: Cognition and Latent Evaluation for Adaptive Routing in End-to-End Autonomous Driving
Yining Xing, Zehong Ke, Zhiyuan Liu +3
End-to-end autonomous driving models often struggle to balance multi-modal maneuver generation with real-time inference constraints. While diffusion models successfully capture div…
MISTY: High-Throughput Motion Planning via Mixer-based Single-step Drifting
Yining Xing, Zehong Ke, Yiqian Tu +3
Multi-modal trajectory generation is essential for safe autonomous driving, yet existing diffusion-based planners suffer from high inference latency due to iterative neural functio…
DriveCode: Domain Specific Numerical Encoding for LLM-Based Autonomous Driving
Zhiye Wang, Yanbo Jiang, Rui Zhou +5
Large language models (LLMs) have shown great promise for autonomous driving. However, discretizing numbers into tokens limits precise numerical reasoning, fails to reflect the pos…
Controllable Traffic Simulation through LLM-Guided Hierarchical Reasoning and Refinement
Zhiyuan Liu, Leheng Li, Yuning Wang +5
Evaluating autonomous driving systems in complex and diverse traffic scenarios through controllable simulation is essential to ensure their safety and reliability. However, existin…