SOTAVerified

Autonomous Driving

Autonomous driving is the task of driving a vehicle 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: Exploring the Limitations of Behavior Cloning for Autonomous Driving)

Papers

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Showing 4901–4950 of 6092 papers

TitleStatusHype
PRIMA: General and Precise Neural Network Certification via Scalable Convex Hull Approximations—0
Predicting Action Tubes—0
Predicting Road Surface Anomalies by Visual Tracking of a Preceding Vehicle—0
Predicting Take-over Time for Autonomous Driving with Real-World Data: Robust Data Augmentation, Models, and Evaluation—0
Predicting the Road Ahead: A Knowledge Graph based Foundation Model for Scene Understanding in Autonomous Driving—0
Predicting Trust Dynamics with Dynamic SEM in Human-AI Cooperation—0
Prediction Accuracy & Reliability: Classification and Object Localization under Distribution Shift—0
Prediction Based Decision Making for Autonomous Highway Driving—0
Prediction by Anticipation: An Action-Conditional Prediction Method based on Interaction Learning—0
PredictionNet: Real-Time Joint Probabilistic Traffic Prediction for Planning, Control, and Simulation—0
Prediction of Occluded Pedestrians in Road Scenes using Human-like Reasoning: Insights from the OccluRoads Dataset—0
Predictions of short-term driving intention using recurrent neural network on sequential data—0
Predictive Heterogeneity: Measures and Applications—0
Predictive Maneuver Planning with Deep Reinforcement Learning (PMP-DRL) for comfortable and safe autonomous driving—0
Improving Predictive Uncertainty Estimation using Dropout -- Hamiltonian Monte Carlo—0
Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing—0
Preference learning along multiple criteria: A game-theoretic perspective—0
Preferential Multi-Objective Bayesian Optimization—0
PreGSU-A Generalized Traffic Scene Understanding Model for Autonomous Driving based on Pre-trained Graph Attention Network—0
Preprocessing Methods of Lane Detection and Tracking for Autonomous Driving—0
Pre-trained Trojan Attacks for Visual Recognition—0
Pre-Trained Vision Models as Perception Backbones for Safety Filters in Autonomous Driving—0
PRIMEDrive-CoT: A Precognitive Chain-of-Thought Framework for Uncertainty-Aware Object Interaction in Driving Scene Scenario—0
Priority-Driven Safe Model Predictive Control Approach to Autonomous Driving Applications—0
Prior Knowledge Input to Improve LSTM Auto-encoder-based Characterization of Vehicular Sensing Data—0
PriorMapNet: Enhancing Online Vectorized HD Map Construction with Priors—0
Privacy-preserving Universal Adversarial Defense for Black-box Models—0
PrivilegedDreamer: Explicit Imagination of Privileged Information for Rapid Adaptation of Learned Policies—0
Privileged to Predicted: Towards Sensorimotor Reinforcement Learning for Urban Driving—0
π-ROAD: a Learn-as-You-Go Framework for On-Demand Emergency Slices in V2X Scenarios—0
ProAI: An Efficient Embedded AI Hardware for Automotive Applications -- a Benchmark Study—0
Probabilistic Approach for Road-Users Detection—0
Probabilistic End-to-End Vehicle Navigation in Complex Dynamic Environments with Multimodal Sensor Fusion—0
Probabilistic model predictive safety certification for learning-based control—0
Probabilistic Object Classification using CNN ML-MAP layers—0
Probabilistic Semantic Mapping for Urban Autonomous Driving Applications—0
Probabilistic Time Series Forecasting for Adaptive Monitoring in Edge Computing Environments—0
Probability Trajectory: One New Movement Description for Trajectory Prediction—0
Procedural Humans for Computer Vision—0
PrognoseNet: A Generative Probabilistic Framework for Multimodal Position Prediction given Context Information—0
Progressive Multi-Modal Fusion for Robust 3D Object Detection—0
Progressive Smoothing for Motion Planning in Real-Time NMPC—0
ProgSG: Cross-Modality Representation Learning for Programs in Electronic Design Automation—0
ProIn: Learning to Predict Trajectory Based on Progressive Interactions for Autonomous Driving—0
Promptable Closed-loop Traffic Simulation—0
Prompt-based Visual Alignment for Zero-shot Policy Transfer—0
Prompt-Guided Environmentally Consistent Adversarial Patch—0
Prompting Multi-Modal Tokens to Enhance End-to-End Autonomous Driving Imitation Learning with LLMs—0
ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos—0
ProphNet: Efficient Agent-Centric Motion Forecasting with Anchor-Informed Proposals—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ReasonNetDriving Score79.95—Unverified
2InterFuserDriving Score76.18—Unverified
3TCPDriving Score75.14—Unverified
4TF++ WPDriving Score66.32—Unverified
5Learning From All Vehicles (LAV)Driving Score61.85—Unverified
6TransFuserDriving Score61.18—Unverified
7TransFuser (Reproduced)Driving Score55.04—Unverified
8TCP (Reproduced)Driving Score47.91—Unverified
9Latent TransFuserDriving Score45.2—Unverified
10GRIADDriving Score36.79—Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC69.17—Unverified
2TransFuserRC56.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC86.91—Unverified
2TransFuserRC78.41—Unverified