Papers Autonomous Driving
“Autonomous Driving” 태그가 달린 논문 8,097편 · 필터 해제
Weather-Aware Domain Adaptation for Street-View Weather Recognition
Adverse conditions such as rain, snow, fog, and dust remain challenging for camera-based perception in autonomous driving. We study multi-class weather recognition from street-view images under domain shift, where most a…
Autonomous DrivingDomain AdaptationMapLightning: Online Vectorized HD Map Construction with 1D Map Tokens
Online vectorized HD map construction is essential for scaling safe autonomous driving and requires accurate, real-time inference. Prior methods typically rely on dense bird's-eye-view (BEV) grids as the intermediate rep…
Online Vectorized HD Map ConstructionTrajectory PredictionAutonomous DrivingEnd-to-End Learning vs. Modular Architectures: Comparative Insights into Autonomous Driving Systems
Autonomous driving systems have become a central focus of intelligent transportation research, with End-to-End Learning and Modular Architectures offering two prominent design paradigms for their implementation. E2E Lear…
Autonomous DrivingEvaluating Physical Consistency and Plausibility in Generative Scenario Models for Autonomous Driving
Generative AI models are increasingly used for scenario generation in autonomous driving. While they can generate realistic-looking scenarios, they often provide limited transparency into learned representations and cons…
Autonomous DrivingTowards Reliable Vision-Language Models for Autonomous Driving
Vision-Language models (VLMs) are increasingly being explored in autonomous driving for tasks such as scene understanding, driving reasoning, decision-making, and end-to-end driving. As their role becomes more prominent,…
Scene UnderstandingAutonomous DrivingDyRAD: Radar Novel View Synthesis for Dynamic Driving Scenes
Reconstructing dynamic driving scenes from recorded sensor data supports closed-loop evaluation of autonomous driving systems by synthesizing observations beyond the original trajectory. Unlike cameras and LiDAR, radar m…
Novel View SynthesisAutonomous DrivingD-JEPA: A Decision-Aligned Latent World Model
Latent world models predict the consequences of actions, but accurate prediction does not guarantee that latent distance reflects which candidate will execute successfully. We identify a decision-local prediction gap: am…
Autonomous DrivingNeuroSymbEAD: A Large Scale Neuro-Symbolic Caption Dataset for Omni-Directional Embodied Autonomous Driving
This paper introduces NeuroSymbEAD, a large-scale neuro-symbolic caption dataset featuring an ego-centric knowledge graph (KG) of static and dynamic objects annotated with classes, categories, heading directions, orienta…
Scene Understanding3D Object DetectionAutonomous DrivingWorld Models for Embodied Intelligence: From Plausible to Controllable to Actionable
World models connect perception and decision-making in embodied intelligence by maintaining hidden state, anticipating consequences, comparing interventions, and adapting when execution departs from expectations. Althoug…
Autonomous DrivingQuantifying Spectral Differences in Vehicle Kinematics Between Production Autonomous and Human-Driven Vehicles Across Driving Scenarios
Differences in vehicle kinematic characteristics between production autonomous vehicles (PAVs) and human-driven vehicles (HVs) have been limitedly investigated by empirical studies. Most recent studies rely on simulation…
Autonomous VehiclesDensity EstimationAutonomous DrivingData-Driven Risk Fields for Safer End-to-End Autonomous Driving
Safety is a fundamental requirement for autonomous driving, yet existing end-to-end driving models still lack explicit risk-aware learning capacities. Existing rule-based risk models provide interpretable safety priors, …
Autonomous DrivingCLFTv2: Efficient Camera-LiDAR Fusion for Semantic Segmentation via Hierarchical Feature Pyramids
Semantic segmentation for autonomous driving requires reliable detection of vulnerable road users (VRUs) despite heavy class imbalance. We introduce CLFTv2, a hierarchical camera-LiDAR fusion framework replacing global V…
Semantic SegmentationAutonomous DrivingA Risk-Sensitive and Uncertainty-Aware Decision-Making and Control Framework for Safe and Robust Autonomous Driving
Reinforcement learning (RL) has demonstrated considerable potential for autonomous driving decision-making. However, its deployment in urban autonomous driving, particularly at highly interactive unsignalized intersectio…
Reinforcement LearningAutonomous DrivingPlannerForge: LLM Agents for Scenario-Based Testing of Motion Planners in Autonomous Driving
Ensuring the safety of autonomous driving is a critical challenge. Scenario-based testing is a systematic process used to validate Autonomous Driving Systems (ADSs), but it remains a fragmented modular pipeline in which …
Autonomous DrivingOne Diffusion Model, Two Roles: Guided Trajectory Planning and Safety-Critical Scenario Generation in Closed-Loop Simulation
Diffusion probabilistic models can capture the multi-modal, interaction-rich distribution of joint future trajectories in driving scenes. We show that a single pretrained diffusion traffic model can serve two complementa…
Trajectory PlanningAutonomous DrivingMotion PlanningMitigating Performance Discrepancy in Cross-Domain 3D Class-Incremental Learning
3D perception plays a crucial role in real-world applications such as autonomous driving, robotics, and AR/VR. In practical scenarios, 3D perception models need to continually adapt to newly emerging 3D object categories…
class-incremental learningAutonomous DrivingPoint CloudsCoLMIN: LLM-based Multi-Decision Path Negotiation for Cooperative Autonomous Driving
Multi-vehicle cooperative autonomous driving enhances the safety and reliability of autonomous driving systems through information sharing among connected vehicles, demonstrating significant potential for improving traff…
Autonomous DrivingShallowStream: Index Shallow then Answer Deep for Streaming Video Understanding
Streaming video understanding is a critical capability for real-world applications, including embodied intelligence, autonomous driving, industrial monitoring, surveillance and early warning, and wearable assistants. How…
Autonomous DrivingReal-Time Scene-Adaptive Tone Mapping for High-Dynamic Range Object Detection
High-dynamic-range (HDR) images, with their rich tone and detail reproduction, hold significant potential to enhance computer vision systems, particularly in autonomous driving. However, most neural networks for embedded…
Autonomous DrivingObject DetectionOpen-Source Autonomous Driving System Analysis and Multi-Disciplinary Hardware-in-the-Loop Research Paradigm with Reinforcement-Learning Testing and Large Language Models
Open-source autonomous driving systems provide an inspectable software foundation for intelligent vehicle research. Under real-vehicle deployment conditions, the recording and review of experimental conditions are import…
Autonomous Driving