Modern smartphones are globally ubiquitous. As such, an increasing number of drivers have their smartphone in their vehicle while driving. These phones are equipped with powerful sensing, processing, and communication capabilities. This provides an opportunity to deploy smartphones in modern telematics and mobile telemetry technologies to enable the collection of driving data. Such data can be exploited to obtain insights regarding the vehicle driving patterns as well as the drivers’ skills. These insights are valuable in many applications including the usage-based insurance, young driver coaching, and fleet management solutions. However, the sensory data provided by a smartphone must be reoriented with respect to the vehicle to be utilized in such applications.
This requires the orientation of the smartphone relative to the vehicle reference system to be estimated through a calibration process. Furthermore, the orientation of a smartphone can vary at any time during a trip due to extraneous factors such as user interaction. This makes the orientation calibration process a challenging task. This paper describes an opportunistic calibration method that continuously monitors a smartphone orientation and compensates for its variation, as necessary. The proposed method relies on the probabilistic fusion of built-in sensors; in particular, the GPS, accelerometer, gyroscope, and magnetometer. The extensive experiments conducted using real-world driving data illustrate the effectiveness of the proposed opportunistic calibration method.