DRIVE-SAFE: Signal Processing and Advanced Information Technologies for improving Driver/Driving Prudence and Accident Reduction
Istanbul Technical University
OTAM Automotive Research Center
In this initiative, we propose to create conditions for prudent driving on highways and roadways with the purposes of reducing accidents caused by driver behavior. Drive-Safe initiative will enable drivers to be prudent by means of signal processing and data fusion techniques. In addition to saving lives, reducing injuries and thus improving the quality of life, significant impact on national and regional economy, goods and services are expected.
To achieve these primary goals, critical data will be collected from multimodal sensors (such as cameras, microphones and other sensors) to build a unique databank on driver behavior. We will develop system and technologies for analyzing the data and automatically determining potentially dangerous situations (such as driver fatigue, distraction, drunk driving, and etc.). Based on the findings from these studies, we will propose systems for warning the drivers and taking other precautionary measures to avoid accidents once a dangerous situation is detected.
In the framework of the "Signal Processing and Advanced Information Technologies for improving Driver/Driving Prudence and Accident Reduction" project, the following papers and a thesis are published:
 - Marian Bartlett, Gwen Littlewort, Javier Movellan, Esra Vural, Kang Lee, Müjdat Çetin, and Aytül Erçil, "Datamining Spontaneous Facial Behavior with Automatic Expression Coding," Verbal and Nonverbal Features of Human-Human and Human-Machine Interaction, A. Esposito, N.G. Bourbakis, N. Avouris, and I. Hatzilygeroudis (eds.), Springer, Lecture Notes in Computer Science 5042, October 2008 (ISBN: 978-3540708711).