Abstract-Driving style can characteristically be divided into two categories: "typical" (non-aggressive) and aggressive. Understanding and recognizing driving events that fall into these categories can aid in vehicle safety systems. Potentiallyaggressive driving behavior is currently a leading cause of traffic fatalities in the United States. More often than not, drivers are unaware that they commit potentially-aggressive actions daily. To increase awareness and promote driver safety, we are proposing a novel system that uses Dynamic Time Warping (DTW) and smartphone based sensor-fusion (accelerometer, gyroscope, magnetometer, GPS, video) to detect, recognize and record these actions without external processing. Our system differs from past driving pattern recognition research by fusing related inter-axial data from multiple sensors into a single classifier. It also utilizes Euler representation of device attitude (also based on fused data) to aid in classification. All processing is done completely on the smartphone.
A DTW and Smartphone based sensor-fusion system, utilizing Euler representation, has been proposed by REF to distinguish between safe and unsafe behaviour.
Driving style recognition using a smartphone as a sensor platform
2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)
2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)
Engineering Computer Science