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自动驾驶

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前言

汇总CVPR2025自动驾驶前沿论文

自动驾驶的轨迹预测论文

Leveraging SD Map to Augment HD Map-based Trajectory Prediction
ModeSeq: Taming Sparse Multimodal Motion Prediction with Sequential Mode Modeling
Adapting to Observation Length of Trajectory Prediction via Contrastive Learning
From Sparse Signal to Smooth Motion: Real-Time Motion Generation with Rolling Prediction Models
Physical Plausibility-aware Trajectory Prediction via Locomotion Embodiment
Towards Generalizable Trajectory Prediction using Dual-Level Representation Learning and Adaptive Prompting
Multiple Object Tracking as ID Prediction
Enduring, Efficient and Robust Trajectory Prediction Attack in Autonomous Driving via Optimization-Driven Multi-Frame Perturbation Framework
Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning
Poly-Autoregressive Prediction for Modeling Interactions

端到端自动驾驶论文

Bridging Past and Future: End-to-End Autonomous Driving with Historical Prediction and Planning
DriveGPT4-V2: Harnessing Large Language Model Capabilities for Enhanced Closed-Loop Autonomous Driving
Distilling Multi-modal Large Language Models for Autonomous Driving
MPDrive: Improving Spatial Understanding with Marker-Based Prompt Learning for Autonomous Driving
DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving
CarPlanner: Consistent Auto-regressive Trajectory Planning for Large-Scale Reinforcement Learning in Autonomous Driving
Don’t Shake the Wheel: Momentum-Aware Planning in End-to-End Autonomous Driving
GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous Driving
SOLVE: Synergy of Language-Vision and End-to-End Networks for Autonomous Driving