### **Context**

Aggressive driving behavior is the leading factor of road traffic accidents. As reported by the **AAA Foundation for Traffic Safety**, 106,727 fatal crashes – 55.7 percent of the total – during a recent four-year period involved drivers who committed one or more aggressive driving actions. Therefore, how to predict dangerous driving behavior quickly and accurately?

### **Solution Approach**

Aggressive driving includes speeding, sudden breaks and sudden left or right turns. All these events are reflected on accelerometer and gyroscope data. Therefore, knowing that almost everyone owns a smartphone nowadays which has a wide variety of sensors, we've designed a data collector application in android based on the accelerometer and gyroscope sensors.

### **Content**

- Sampling Rate: 2 samples (rows) per second.
- Gravitational acceleration: removed.
- Sensors: Accelerometer and Gyroscope.
- Data: 
   1.  Acceleration (X,Y,Z axis in meters per second squared (m/s2))
   2.  Rotation (X,Y, Z axis in degrees per second (°/s))  
   3.  Classification label (SLOW, NORMAL, AGGRESSIVE)
   4.  Timestamp (time in seconds)
- Driving Behaviors:
   1.  Slow
   2.  Normal
   3.  Aggressive
- Device: Samsung Galaxy S21

### **Articles**
- [Building a Driving Behaviour Dataset](http://rochi.utcluj.ro/articole/10/RoCHI2022-Cojocaru-I-1.pdf)
- [Driver Behaviour Analysis based on Deep Learning Algorithms](http://rochi.utcluj.ro/articole/10/RoCHI2022-Cojocaru-I-2.pdf)

### **Authors**

- Paul-Stefan Popescu
- Ion Cojocaru