The article discusses how different factors like road design, traffic volume, and driver behavior affect the likelihood of traffic crashes. Researchers used artificial neural networks to predict crash rates on Kansas roads and found that road layout and traffic flow significantly impact crash rates. They also discovered that young drivers aged 18-20 are most likely to be involved in crashes, and passenger cars are the most common vehicle type in crashes. These findings can help the Kansas Department of Transportation make better decisions about road design and traffic planning to improve safety.