From the 1 of 8 linked papers with an AI index.
8 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…
From Scene to Object: Text-Guided Dual-Gaze Prediction
Zehong Ke, Yanbo Jiang, Jinhao Li +5
Interpretable driver attention prediction is crucial for human-like autonomous driving. However, existing datasets provide only scene-level global gaze rather than fine-grained obj…
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…
Driving risk emerges from the required two-dimensional joint evasive acceleration
Hao Cheng, Yanbo Jiang, Wenhao Yu +9
Most autonomous driving safety benchmarks use time-to-collision (TTC) to assess risk and guide safe behaviour. However, TTC-based methods treat risk as a one-dimensional closing pr…
SymDrive: Realistic and Controllable Driving Simulator via Symmetric Auto-regressive Online Restoration
Zhiyuan Liu, Daocheng Fu, Pinlong Cai +5
High-fidelity and controllable 3D simulation is essential for addressing the long-tail data scarcity in Autonomous Driving (AD), yet existing methods struggle to simultaneously ach…