In the United States, traffic crashes claim the lives of 30,000 people every year and is the leading cause of death for 5-24 year olds. Driver error is the leading factor in over 90 percent of motor vehicle crashes, with the roadway and the vehicle each only accounting for about 2 percent of crashes. In the United States, nearly a third of fatal crashes are due to speeding and therefore, a critical step in improving traffic safety is research aimed to reduce speeding, such as crash data analysis, outreach campaigns, targeted enforcement, and understanding speed selection. In this dissertation, a multi-faceted approach was taken to improve roadway safety by examining the speeding-related crash designation, improving speed limit setting practices, and understanding the causes of speeding. Multiple experiments were conducted under this overarching goal. These experiments included an analysis of speeding-related crashes in Massachusetts, a naturalistic driving study, and a driving simulator study which investigated the causes of speeding. Collectively, the findings from these experiments can expand upon existing speed prediction models, improve crash data influence speed limit setting practices, guide speed management programs such as speed enforcement, and be used in public safety outreach campaigns
