Latest Articles for Traffic Safety

Quantum radar offers improved detection by using entangled light particles.

A new method enhances trajectory predictions for autonomous vehicles in complex environments.

New model aims to enhance traffic safety through accurate accident predictions.

Air pollution poses serious health risks, especially for asthma sufferers.

Research reveals how gestures can enhance safety for pedestrians and self-driving cars.

New model helps self-driving cars merge safely into busy traffic.

This article explores the TUMTraf-V2X dataset and its impact on self-driving car safety.

A review of road safety data management in Ethiopia to improve road safety.

Research explores how interconnected eHMIs can improve communication between AVs and pedestrians.

Introducing a new model for better predicting vehicle movements in traffic.

New methods aim to enhance vehicle control in connected and automated platoons.

New model enhances pedestrian tracking accuracy using monocular cameras.

UP-CrackNet offers a new approach to detecting road cracks with less human involvement.

This paper presents a formal method for testing traffic disturbances in autonomous vehicles.

A new method improves self-driving car training through human-like interaction.

This study examines pediatric femoral shaft fractures and treatment outcomes in Tanzania.

UniV2X enhances autonomous driving through vehicle-infrastructure collaboration.

New methods improve safety by predicting out-of-sight pedestrian movements for autonomous vehicles.

A new approach for realistic traffic scenarios in autonomous vehicle testing.

A technology-driven approach to improve taxi safety and compliance.

A new framework aims to reduce accidents at urban intersections using connected vehicles.

A new method assesses pedestrian risks at crossings using real-time data.

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

Real-world data enhances automated driving systems' safety via advanced simulations.

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

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

Examining the shift to maneuver-based testing for automated vehicles.

A new method enhances trajectory predictions for safer autonomous driving.

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

Research uses advanced CNNs to detect distracted driving, improving road safety.

New technology improves vehicle communication and safety using electromagnetic skins.

A new method enhances data sharing among autonomous vehicles for better traffic safety.

A new method helps self-driving cars handle sudden changes safely.

A review of machine learning methods for predicting traffic accidents and improving road safety.

Study enhances lane-changing strategies for self-driving cars in mixed traffic.

Self-driving cars use rule-based systems for safer road navigation and decision-making.

A new framework enhances testing scenarios for autonomous vehicles in parking garages.

This article examines how adding lanes affects accident rates on freeways.

Improving safety and efficiency in automated vehicles through better trajectory predictions.

A new method enhances safety by accurately predicting Time to Collision using event-based cameras.