Electronic Thesis and Dissertation Repository


Doctor of Philosophy


Computer Science


Dr. Steven Beauchemin


World-wide injuries in vehicle accidents have been on the rise in recent

years, mainly due to driver error. The main objective of this research is to

develop a predictive system for driving maneuvers by analyzing the cognitive

behavior (cephalo-ocular) and the driving behavior of the driver (how the vehicle

is being driven). Advanced Driving Assistance Systems (ADAS) include

different driving functions, such as vehicle parking, lane departure warning,

blind spot detection, and so on. While much research has been performed on

developing automated co-driver systems, little attention has been paid to the

fact that the driver plays an important role in driving events. Therefore, it

is crucial to monitor events and factors that directly concern the driver. As

a goal, we perform a quantitative and qualitative analysis of driver behavior

to find its relationship with driver intentionality and driving-related actions.

We have designed and developed an instrumented vehicle (RoadLAB) that is

able to record several synchronized streams of data, including the surrounding

environment of the driver, vehicle functions and driver cephalo-ocular behavior,

such as gaze/head information. We subsequently analyze and study the

behavior of several drivers to find out if there is a meaningful relation between

driver behavior and the next driving maneuver.