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

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Showing 1941–1950 of 2605 papers

TitleStatusHype
Trajectory Planning for Autonomous Vehicles Using Hierarchical Reinforcement LearningCode1
Behavior Planning at Urban Intersections through Hierarchical Reinforcement Learning—0
Reactive motion planning with probabilistic safety guarantees—0
Motion Prediction on Self-driving Cars: A Review—0
IDE-Net: Interactive Driving Event and Pattern Extraction from Human Data—0
A Scenario-Based Development Framework for Autonomous Driving—0
SLAM in the Field: An Evaluation of Monocular Mapping and Localization on Challenging Dynamic Agricultural Environment—0
Optimizing Mixed Autonomy Traffic Flow With Decentralized Autonomous Vehicles and Multi-Agent RLCode1
Self-awareness in intelligent vehicles: Feature based dynamic Bayesian models for abnormality detection—0
Learning Personalized Discretionary Lane-Change Initiation for Fully Autonomous Driving Based on Reinforcement Learning—0
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Benchmark Results

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