Abstract
This paper introduces a driver identification system architecture for public transport which utilizes only acceleration sensor data. The system architecture consists of three main modules which are the data collection, data preprocessing, and driver identification module. Data were collected from real operation of campus shuttle buses. In the data preprocessing module, a filtering module is proposed to remove the inactive period of the public transport data. To extract the unique behavior of the driver, a histogram of acceleration sensor data is proposed as a main feature of driver identification. The performance of our system is evaluated in many important aspects, considering axis of acceleration, sliding window size, number of drivers, classifier algorithms, and driving period. Additionally, the case study of impostor detection is implemented by modifying the driver identification module to identify a car thief or carjacking. Our driver identification system can achieve up to 99% accuracy and the impostor detection system can achieve the F1 score of 0.87. As a result, our system architecture can be used as a guideline for implementing the real driver identification system and further driver identification researches.
Highlights
Twenty billion units is the number of the Internet of Things (IoT) that is predicted to be installed in 2020 [1,2,3]
Technology of sensors and communication devices dramatically increases this number of connected things
We have proposed a public transport driver identification system architecture which utilized only a single acceleration sensor
Summary
Twenty billion units is the number of the Internet of Things (IoT) that is predicted to be installed in 2020 [1,2,3]. Consumer vehicles are equipped with a lot of sensors in order to provide driver-assistant services, such as adaptive cruise control, automatic parking, and automatic emergency breaking. These sensors in vehicles lead to an advancement in transportation research. One of the popular research topics is the study of the driving style to detect the driver’s behavior. Apart from detecting driving style, if a driver has his own driving style, the driver himself could be identified This leads to the driver identification research that can automatically identify an individual driver using sensors in the vehicle
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
