New research from PhD candidate, Yasser Abdulrahim Alobidan, shows how AI can help predict the severity of road crashes.
“Road crashes remain a major public safety problem worldwide, causing loss of life, serious injuries and significant economic costs,” Yasser says. “The problem is not only preventing crashes but also understanding why some crashes are more severe than others.”
Yasser’s research brought together evidence from studies around the world to examine how AI can make better use of road and crash data to identify patterns in serious accidents.
“Newer AI approaches can often identify complex patterns in crash data better than traditional methods, especially when they combine information such as road conditions, weather, traffic and driver behaviour,” he explains.
However, he also found that high accuracy is not enough on its own.
“My review highlights the need for systems that are not only accurate, but also understandable, adaptable to different locations and practical for real-world road safety decisions.”
Yasser hopes his research will ultimately help improve road safety and reduce the consequences of serious crashes.
“By identifying the factors associated with more severe crashes, AI could support road authorities and emergency services in making faster and better-informed decisions, such as prioritising emergency response and targeting safety measures where they are most needed,” he says.
“In the longer term, this could help make AI-based road safety tools more practical, trustworthy and useful in real-world transport systems.”
