Self-driving cars rely on artificial intelligence to predict where nearby cars will go. But when those predictions don’t match reality, that discrepancy can potentially lead to crashes and less safe roadways. That’s why a recent study from the University of Georgia developed a new AI model to make self-driving cars safer.
Tag: Road Safety
Road features that predict crash sites identified in new machine-learning model
Issues such as abrupt changes in speed limits and incomplete lane markings are among the most influential factors that can predict road crashes, finds new research by University of Massachusetts Amherst engineers.
New $26 Million NSF Engineering Research Center to Advance Future of Smart Streetscapes
FAU has landed a major NSF Engineering Research Center with Columbia University, Rutgers University, the University of Central Florida, and Lehman College.
Driving in the Snow is a Team Effort for AI Sensors
Nobody likes driving in a blizzard, including autonomous vehicles. To make self-driving cars safer on snowy roads, Michigan Tech engineers look at the problem from the car’s point of view–its sensors.
Johns Hopkins Center for Injury Research and Policy at Bloomberg School of Public Health Co-Hosts Panel on Road Safety, Tuesday, May 11 at 2 PM EDT
The Johns Hopkins Center for Injury Research and Policy at the Johns Hopkins Bloomberg School of Public Health is co-hosting an online panel discussion at 2 p.m., Tuesday, May 11, EDT, with the Institute of Transportation Engineers.
Complex Fluid Dynamics May Explain Hydroplaning
Research into hydroplaning currently uses a test track equipped with a transparent window embedded in the ground. The area above is flooded and a tire rolling over the window is observed with a high-speed camera. Investigators in France have developed a more sophisticated approach involving fluorescent seeding particles to visualize the flow and used a sheet of laser light to illuminate the area. They discuss their work in Physics of Fluids.