title: A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors.
abstract: In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution) and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden) can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects.
authors: Advanced Sensor and Integrated System Lab, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China. wml15@mails.tsinghua.edu.cn.
authors: Minglin
authors: M
authors: Wu
authors: Advanced Sensor and Integrated System Lab, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China. zhang_sh@tsinghua.edu.cn.
authors: Sheng
authors: S
authors: Zhang
authors: Advanced Sensor and Integrated System Lab, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China. dongyuhan@sz.tsinghua.edu.cn.
authors: Yuhan
authors: Y
authors: Dong
mesh_terms: D000465:Algorithms; D001334:Automobile Driving; D006801:Humans; D000069550:Machine Learning; D009038:Motion
keywords: Kalman filter; adaptive time window; classification; data change rule; driving behavior recognition; motion sensors; physical model