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- Title
Recognizing Driving Behavior and Road Anomaly using Smartphone Sensors.
- Authors
Ali, Aya Hamdy; Atia, Ayman; Mostafa, Mostafa-Sami M.
- Abstract
Road traffic accidents are caused 1.25 million deaths per year worldwide. To improve road safety and reducing road accidents, a recognition method for driving events is introduced in this paper. The proposed method detected and classified both driving behaviors and road anomalies patterns based on smartphone sensors (accelerometer and gyroscope). k-Nearest Neighbor and Dynamic Time Warping algorithms were utilized for method evaluation. Experiments were conducted to evaluate k-nearest neighbor and dynamic time warping algorithms accuracy for road anomalies and driving behaviors detection, moreover, driving behaviors classification. Evaluation results showed that k-nearest neighbor algorithm detected road anomalies and driving behaviors with total accuracy 98.67%. Dynamic time warping algorithm classified (normal and abnormal) driving behaviors with total accuracy 96.75%.
- Publication
International Journal of Ambient Computing & Intelligence, 2017, Vol 8, Issue 3, p22
- ISSN
1941-6237
- Publication type
Article
- DOI
10.4018/IJACI.2017070102