Latest Articles for Autonomous Vehicles

Assessing image translation techniques in self-driving car testing.

New methods enhance safety by measuring confidence in self-driving vehicle decisions.

Introducing a new framework for realistic pedestrian animations in AV training.

This method improves the safety of self-driving cars through enhanced detection techniques.

A new system predicts actions of pedestrians and drivers, enhancing road safety.

Research focuses on how autonomous vehicles can match human driving styles for comfort.

M3Net enhances LiDAR segmentation for self-driving cars by integrating diverse datasets and sensors.

Addressing communication issues for safer and more efficient vehicle platooning.

A method for training agents to follow rules while maximizing rewards.

Federated learning faces new poisoning attacks, threatening safety in self-driving technology.

A new method improves safety in high-dimensional reachability for autonomous vehicles.

BadFusion uses camera data to launch backdoor attacks on self-driving systems.

New AI model enhances understanding of images in three dimensions.

PAFOT improves safety testing for self-driving cars through advanced simulation techniques.

A fresh approach to assessing how drivers communicate and interact on the road.

DriveWorld enhances self-driving technology by analyzing spatial and temporal data.

Combining LiDAR and camera data to improve self-driving technology efficiency.

A new algorithm enhances safety and efficiency in connected autonomous vehicles.

This study develops a controller for autonomous vehicles to enhance safety in traffic.

New system protects autonomous vehicles from GPS spoofing attacks.

This article discusses a distributed method for traffic management using connected vehicles.

NaviSlim optimizes drone navigation by adapting resources to environments.

Smart roadside infrastructure enhances safety and efficiency for self-driving cars.

Exploring semi-on-demand hybrid transit routes for better access and efficiency.

EdgeLoc combines traditional and modern methods for better vehicle location tracking.

A look into chattering in control and its impact on system efficiency.

Exploring how autonomous vehicles can safely integrate into busy airspace.

New methods improve vehicle tracking accuracy using radar and camera data.

A method for verifying safety in self-driving cars and drones using neural networks.

A method to secure neural networks against vulnerabilities in memory.

A new toolbox improves LiDAR segmentation for safer self-driving cars.

This paper examines how sensors enhance decisions despite incomplete data.

A new method uses basic sensors to create detailed maps for autonomous vehicles.

A new approach enhances self-driving cars by mimicking human thinking patterns.

Enhancing LiDAR systems for better object recognition in autonomous vehicles.

Techniques for guiding robots to specific locations while avoiding obstacles.

UniTraj addresses the challenges of multi-agent trajectory modeling with a unified approach.

Simulations play a vital role in assessing the safety of autonomous vehicles.

A look into contract-based design for hybrid systems and their complexities.

WeiPer improves out-of-distribution detection in machine learning models using weight adjustments.