Driver Behavior Analysis for Safe Driving: A Survey


KAPLAN S., GÜVENSAN M. A. , YAVUZ A. G. , KARALURT Y.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, cilt.16, 2015 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 16 Konu: 6
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1109/tits.2015.2462084
  • Dergi Adı: IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Özet

Driver drowsiness and distraction are two main reasons for traffic accidents and the related financial losses. Therefore, researchers have been working for more than a decade on designing driver inattention monitoring systems. As a result, several detection techniques for the detection of both drowsiness and distraction have been proposed in the literature. Some of these techniques were successfully adopted and implemented by the leading car companies. This paper discusses and provides a comprehensive insight into the well-established techniques for driver inattention monitoring and introduces the use of most recent and futuristic solutions exploiting mobile technologies such as smartphones and wearable devices. Then, a proposal is made for the active of such systems into car-to-car communication to support vehicular ad hoc network's (VANET's) primary aim of safe driving. We call this approach the dissemination of driver behavior via C2C communication. Throughout this paper, the most remarkable studies of the last five years were examined thoroughly in order to reveal the recent driver monitoring techniques and demonstrate the basic pros and cons. In addition, the studies were categorized into two groups: driver drowsiness and distraction. Then, research on the driver drowsiness was further divided into two main subgroups based on the exploitation of either visual features or nonvisual features. A comprehensive compilation, including used features, classification methods, accuracy rates, system parameters, and environmental details, was represented as tables to highlight the (dis) advantages and/or limitations of the aforementioned categories. A similar approach was also taken for the methods used for the detection of driver distraction.