Konferens: FAST-zero'15: 3rd International symposium on future active safety technology toward zero traffic accidents, 2015, Gothenburg

This study proposes a method to extract the unique driving signatures of individual drivers. We assume that each driver has a unique driving signature that can be represented in a k dimensional principal driving component (PDC) space. We propose a method to extract this signature from sensor data. Furthermore, we suggest that drivers with similar driving signatures can be categorized into driving style classes such as aggressive or careful driving. In our experiments, 122 different drivers have driven the same path on Nagoya city express highway with the same instrumented car. GPS, speed, acceleration, steering wheel position and pedal operations have been recorded. Clustering methods have been used to identify driving signatures.