Latest Articles for Autonomous Vehicles

A new method improves LiDAR place recognition for robots and self-driving cars.

A new method enhances the detection of road hazards for advanced driving systems.

This study highlights the importance of object detection in construction zones for self-driving cars.

MemFusionMap improves real-time HD mapping using past frame information.

A new method enhances accuracy in speed estimation for drones using radar and accelerometer data.

3DIOC efficiently determines control objectives from data without needing system models.

Research reveals vulnerabilities in AV lane detection through negative shadows.

Innovative methods enhance understanding of surroundings for self-driving vehicles.

A new dataset aims to improve machine learning with dynamic vision sensor data.

This model improves vehicle navigation by combining localization and path planning techniques.

CASPFormer innovates trajectory prediction using bird’s eye view images.

SPARQ enhances safety monitoring for autonomous vehicles by addressing perception failures.

A new approach improves self-driving car safety through counterfactual examples.

A new framework to evaluate the effectiveness of vision-based positioning systems.

Enhancements in LiDAR perception improve performance in multi-sensor environments.

A method to manage conflicting sensor data in autonomous vehicles for improved safety.

This model improves depth estimation while being resource-efficient and easy to use.

A new method helps self-driving boats avoid collisions in busy waters.

New framework enhances video understanding in dim conditions using event cameras.

Examining how vehicle platooning can enhance traffic safety and flow.

PLATYPUS improves 3D point cloud clarity for better machine perception.

HeightMapNet improves mapping for self-driving cars by enhancing accuracy and detail.

Explore how new technologies improve the accuracy of autonomous systems in various tasks.

Polar R-CNN innovates lane detection, improving efficiency and performance.

Learn how self-driving cars avoid accidents using Evasive Minimum Risk Maneuvering.

Learn how robots create maps of their surroundings using advanced techniques.

Learn how machines estimate depth and adapt to different environments.

A new method blends visible and thermal images for better depth estimation.

DSceneKG offers a rich resource for training AI in real-world driving situations.

ISAC combines sensing and communication to enhance mobile network capabilities.

LidaRefer improves outdoor object recognition for autonomous vehicles.

Researchers tackle challenges of teaching self-driving cars through imitation and learning.

Exploring how self-driving cars interact with human-driven vehicles for safety.

Learn how scientists are training robot cars to drive safely off-road.

A new approach improves how computers learn from experience.

PKF improves object tracking accuracy in complex environments.

Learn how model-free control helps machines operate with minimal information.

Researchers enhance recognition of traffic lights for self-driving cars in poor weather.

A new method enhances drone reliability and adaptability during flight.

Study enhances video understanding through motion-focused questions and visual answers.