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 576–600 of 2605 papers

TitleStatusHype
HighwayLLM: Decision-Making and Navigation in Highway Driving with RL-Informed Language Model—0
Uncertainty-Aware DRL for Autonomous Vehicle Crowd Navigation in Shared SpaceCode1
Mutual Information Analysis in Multimodal Learning Systems—0
Generalized Multi-Objective Reinforcement Learning with Envelope Updates in URLLC-enabled Vehicular Networks—0
Deep Koopman Operator-Informed Safety Command Governor for Autonomous Vehicles—0
Incorporating ESO into Deep Koopman Operator Modelling for Control of Autonomous Vehicles—0
*: Improving the 3D detector by introducing Voxel2Pillar feature encoding and extracting multi-scale features—0
Analyzing and Enhancing Queue Sampling for Energy-Efficient Remote Control of Bandits—0
CarDreamer: Open-Source Learning Platform for World Model based Autonomous DrivingCode3
A Distributed Approach to Autonomous Intersection Management via Multi-Agent Reinforcement LearningCode0
Edge Computing for IoT: Novel Insights from a Comparative Analysis of Access Control Models—0
GPS-IMU Sensor Fusion for Reliable Autonomous Vehicle Position Estimation—0
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous DrivingCode1
Fairness in Reinforcement Learning: A Survey—0
Autonomous Driving with a Deep Dual-Model Solution for Steering and Braking Control—0
GraphRelate3D: Context-Dependent 3D Object Detection with Inter-Object Relationship Graphs—0
Switched Vector Field-based Guidance for General Reference Path Following in Planar Environment—0
Multi-level Personalized Federated Learning on Heterogeneous and Long-Tailed Data—0
Shaping the Future of Urban Mobility: Insights into Autonomous Vehicle Acceptance in Shanghai Through TAM and Perceived Risk Analysis—0
A Survey on Occupancy Perception for Autonomous Driving: The Information Fusion PerspectiveCode4
Novel Actor-Critic Algorithm for Robust Decision Making of CAV under Delays and Loss of V2X Data—0
Radar Fields: Frequency-Space Neural Scene Representations for FMCW Radar—0
TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characters—0
3D LiDAR Mapping in Dynamic Environments Using a 4D Implicit Neural RepresentationCode2
How Good is my Video LMM? Complex Video Reasoning and Robustness Evaluation Suite for Video-LMMs—0
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Benchmark Results

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