SOTAVerified

Autonomous Vehicles

Autonomous vehicles is the task of making a vehicle that can guide itself without human conduction.

Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.

( Image credit: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 626–650 of 2605 papers

TitleStatusHype
Achieving Real-Time Object Detection on MobileDevices with Neural Pruning Search—0
Backup Plan Constrained Model Predictive Control with Guaranteed Stability—0
Analyzing Deep Learning Representations of Point Clouds for Real-Time In-Vehicle LiDAR Perception—0
A Discrete-time Dynamical Model for Optimal Dispatching and Rebalancing of Autonomous Mobility-on-Demand Systems—0
Deep Reinforcement Learning Algorithms for Hybrid V2X Communication: A Benchmarking Study—0
Analyzing Closed-loop Training Techniques for Realistic Traffic Agent Models in Autonomous Highway Driving Simulations—0
A Visual Neural Network for Robust Collision Perception in Vehicle Driving Scenarios—0
A Virtual Environment with Multi-Robot Navigation, Analytics, and Decision Support for Critical Incident Investigation—0
Analyzing and Enhancing Queue Sampling for Energy-Efficient Remote Control of Bandits—0
Deep Reinforcement-Learning-based Driving Policy for Autonomous Road Vehicles—0
Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception—0
Analyze Drivers' Intervention Behavior During Autonomous Driving -- A VR-incorporated Approach—0
Autonomy and Unmanned Vehicles Augmented Reactive Mission-Motion Planning Architecture for Autonomous Vehicles—0
Addressing the IEEE AV Test Challenge with Scenic and VerifAI—0
Autonomy 2.0: The Quest for Economies of Scale—0
Autonomous Vehicle Visual Signals for Pedestrians: Experiments and Design Recommendations—0
Analytical Safety Bounds for Trajectory Following Controllers in Autonomous Vehicles—0
Accurate Trajectory Prediction for Autonomous Vehicles—0
Collaboration Between the City and Machine Learning Community is Crucial to Efficient Autonomous Vehicles Routing—0
Autonomous Vehicles that Interact with Pedestrians: A Survey of Theory and Practice—0
Analysis over vision-based models for pedestrian action anticipation—0
Autonomous Vehicles that Alert Humans to Take-Over Controls: Modeling with Real-World Data—0
Autonomous Vehicles Meet the Physical World: RSS, Variability, Uncertainty, and Proving Safety (Expanded Version)—0
Analysis of the Memorization and Generalization Capabilities of AI Agents: Are Continual Learners Robust?—0
Addressing Data Annotation Challenges in Multiple Sensors: A Solution for Scania Collected Datasets—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BAAMA3DP22.85—Unverified
2GSNetA3DP20.21—Unverified