Driving Style Recognition System Using Smartphone Sensors Based on Fuzzy Logic

Every 24 seconds, someone dies on the road due to road accidents and it is the 8th leading cause of death and the first among children aged 15–29 years. 1.35 million people globally die every year due to road traffic crashes. An additional 20–50 million suffer from non-fatal injuries, often resulting in long-term disabilities. This costs around 3% of Gross Domestic Product to most countries, and it is a considerable economic loss. The governments have taken various measures such as better road infrastructures and strict enforcement of motor-vehicle laws to reduce these accidents. However, there is still no remarkable reduction in the number of accidents. To ensure driver safety and achieve vision of zero accidents, there is a great need to monitor drivers’ driving styles. Most of the existing driving behavior monitoring solutions are based on expensive hardware sensors. As most people are using smartphones in the modern era, a system based on mobile application is proposed, which can reduce the cost for developing intelligent transport systems (ITS) to a large extent. In this paper, we utilize the accelerometer sensor data and the global positioning system (GPS) sensor deployed in smartphones to recognize driving and speeding events. A driving style recognition system based on fuzzy logic is designed to classify different driving styles and control reckless driving by taking the longitudinal/lateral acceleration and speed as input parameters. Thus, the proposed system uses fuzzy logic rather than taking the crisp values of the sensors. Results indicate that the proposed system can classify reckless driving based on fuzzy logic and, therefore, reduce the number of accidents.