Research at Colorado State University shows that action-conveying and emotionally motivated signs are more effective at influencing pedestrian safety and decision-making at railroad crossings.
Researchers at North Dakota State University improved commercial vehicle weight monitoring accuracy by more than 90% by combining traditional weigh-in-motion systems with machine learning techniques and advanced sensor data to integrate information on temperature fluctuations, pavement surface conditions, and vehicle dynamics.
Researchers at Colorado State University have developed an automated pothole detection tool, which combines visible and thermal images to reliably identify potholes under various conditions, particularly in regions with challenging weather.
Researchers at Colorado State University studied various approaches to eco-driving in connected autonomous vehicles to learn how best to evaluate the methods for energy economy. Eco-driving is a strategy designed to reduce fuel consumption by minimizing accelerations and unnecessary braking events.
