Driver Behavior Extraction from Videos in Naturalistic Driving Datasets with 3D ConvNets

DRIVER BEHAVIOR DURING LANE CHANGE FROM THE 100 - CAR NATURALISTIC DRIVING STUDY Rong

Lane changes with the intention to overtake the vehicle in front are especially challenging scenarios for forward collision warning (FCW) designs. These overtaking maneuvers can occur at high relative vehicle speeds and often involve no brake and/or turn signal application. Therefore, overtaking presents the potential of erroneously triggering the FCW. A better understanding of lane change even...

Warning Reliability and Driver Performance in Naturalistic Driving

OBJECTIVE This study examines how naturalistic driving performance is influenced by the perceived reliability of an in-vehicle warning system using a unique measure of perceived reliability. BACKGROUND Prior studies of warning reliability conducted in simulator and test-track experiments demonstrate that the objective reliability of a warning can influence a driver's responsiveness to that wa...

Privacy Protection for Large Scale Naturalistic Driving Videos

A common pool of naturalistic driving data is necessary to develop and compare algorithms that infer driver behavior, in order to improve driving safety. The SHRP 2 naturalistic driving study (NDS) is currently collecting such data for the past two years which will result in approximately 4 petabytes of data, 1 million hours of video, 3000 subjects, 5 million trips, 33 million miles driven and ...

Individual Driver Risk Analysis Using Naturalistic Driving Data

Modeling Naturalistic Driver Behavior in Traffic Using Machine Learning

This research is focused on driver behavior in traffic, especially during car-following situations and safety critical events. Driving behavior is considered as a human decision process in this research which provides opportunities for an artificial driver agent simulator to learn according to naturalistic driving data. This thesis presents two mechine learning methodologies that can be applied...