Master of Science in Civil Engineering (MSCE)


Civil and Environmental Engineering

Document Type



Distracted driving has long been acknowledged as one of the leading causes of death or injury in roadway crashes. The focus of past research has been mainly on the change in driving performance due to distracted driving. However, only a few studies attempted to predict the type of distraction based on driving performance measures. In addition, past studies have proven that driving performance is influenced by the drivers’ socioeconomic characteristics, while not many studies have attempted to quantify that influence. In essence, this study utilizes the rich SHRP 2 Naturalistic Driving Study (NDS) database to (a) develop a model for detecting the likelihood of a driver’s involvement in secondary tasks from distinctive attributes of driving performance, and (b) develop a grading system to quantify the crash risk associated with socioeconomic characteristics and distracted driving. The results show that the developed neural network models were able to detect the drivers’ involvement in calling, texting, and passenger interaction with an accuracy of 99.6%, 99.1%, and 100%, respectively. These results show that the selected driving performance attributes were effective in detecting the associated secondary tasks with driving performance. On the other hand, the grading system was developed by three main parameters: the crash risk coefficient, the significance level coefficient, and the category contribution coefficient. At the end, each driver’s crash risk index could be calculated based on his or her socioeconomic characteristics. The developed detection models and the systematic grading process could assist the insurance company to identify a driver’s probability of conducting distracted driving and assisting the development of cellphone banning regulation by states’ Departments of Transportation.



Document Availability at the Time of Submission

Release the entire work immediately for access worldwide.

Committee Chair

Ishak, Sherif