HMM-based driving behavior recognition for in-car control service

The purpose of this study is to present an approach to analyze and recognize the driver posture. By using the wearable device, the sensing data of the driving behavior postures can be collected and calibrated. The calibrated data is as the input parameters of driving behavior modeling. Then, the Hidden Markov Model (HMM) is utilized to establish the driving behavior posture models. The HMM model can recognize 7 kinds of head postures. Moreover, the static indoor environment and dynamic in-car environment are considered in modeling process. Finally, the constructed driving behavior model can apply to in-car service to provide driver more convenient control service.