Latest Articles for Autonomous Vehicles

A novel approach to safeguard sensitive data captured by self-driving cars.

Research on detection-segmentation networks enhances safety in self-driving cars.

BOTT offers an innovative approach for tracking 3D objects in self-driving cars.

CLLD enhances lane detection under tough conditions using self-supervised learning.

This article explores how sensor fusion enhances self-driving vehicle safety and efficiency.

This study improves traffic sign recognition using enhanced image techniques.

A new method improves shadow detection by separating layers.

A new method enhances motion forecasting using self-supervised learning strategies.

Federated Learning enhances connected vehicle safety while protecting user data.

A new framework enhances 3D model accuracy using partial point clouds for self-driving cars.

VBMO offers a method for efficient path planning with multiple objectives.

ELiOT enhances LiDAR odometry methods for improved robot localization.

DiffSeg offers a new way to segment images without labeled data.

A new method predicts driver behavior and enhances safety in hybrid traffic.

A method for segmenting LiDAR data without manual labels using temporal analysis.

A new approach to AV localization focuses on flexibility and safety.

New features enhance how AVs learn driving styles for safer interactions.

SPROUT enhances safety by detecting misclassifications in machine learning classifiers.

A study on using AI to enhance driverless racing in competitions.

A new model combines neural networks and choice models for safer driving predictions.

MapPrior improves BEV perception, enhancing accuracy and safety for autonomous vehicles.

A new method combines depth estimation and segmentation to enhance autonomous vehicle safety.

Examining how to enhance AV safety by measuring sensor uncertainty.

New methods improve performance of autonomous racing vehicles.

This study examines how eye tracking enhances the performance of Vision Transformers in driving tasks.

A new method improves traffic control using decentralized principles for energy efficiency.

Radar data accumulation can boost object detection in autonomous vehicles.

This article presents an innovative approach to improve traffic sign recognition.

A new framework aims to optimize EAV operations in urban areas.

SQLdepth enhances depth estimation by learning from motion in scenes.

The NTU4DRadLM dataset enhances SLAM research by integrating key sensors for challenging environments.

A new method that combines monocular and binocular depth estimation for enhanced accuracy.

New method improves 3D modeling from 2D images while overcoming learning challenges.

A new method enhances prediction reliability in machine learning models.

A novel approach allows unmanned ground vehicles to navigate in GPS-denied areas.

A new method for safe robot navigation considering physical risks in complex environments.

Motion prediction is vital for safe autonomous vehicle operation, enhancing traffic flow and decision making.

Learn how robots enhance mapping accuracy by filtering out misleading data.

A new approach enhances road mapping accuracy using satellite imagery.

Innovative methods improve the safety and accuracy of autonomous vehicle navigation.