Title: Identification of the driving style for the adaptation of assistance systems

Authors: Görkem Büyükyildiz; Olivier Pion; Christoph Hildebrandt; Martin Sedlmayr; Roman Henze; Ferit Küçükay

Addresses: Institute of Automotive Engineering, Hans-Sommer-Str. 4, 38106 Braunschweig, Germany ' Institute of Automotive Engineering, Hans-Sommer-Str. 4, 38106 Braunschweig, Germany ' Institute of Automotive Engineering, Hans-Sommer-Str. 4, 38106 Braunschweig, Germany ' Institute of Automotive Engineering, Hans-Sommer-Str. 4, 38106 Braunschweig, Germany ' Institute of Automotive Engineering, Hans-Sommer-Str. 4, 38106 Braunschweig, Germany ' Institute of Automotive Engineering, Hans-Sommer-Str. 4, 38106 Braunschweig, Germany

Abstract: Reliable knowledge of specific driver characteristics is important for the adaptation of assistance systems to the driver. The increased safety and comfort based on this knowledge can improve customer acceptance. This study presents a method of identifying specific driver characteristics, i.e. a personal 'fingerprint'. This can be used to draw conclusions about the driving style, age and performance of the driver. To identify the fingerprint, the driver is classified based on the individual driver behaviour, and longitudinal and lateral control behaviour are analysed. The method of identifying the driving style and its implementation into the vehicle using a 'driving style identifier' are the main focuses of this paper. To improve the identifier, lane camera and radar data is taken into account in addition to vehicle signals, such as velocity, longitudinal and lateral acceleration. Several examples of the process of determining the objective parameters from longitudinal and lateral control behaviour are illustrated.

Keywords: driver behaviour modelling; driver monitoring; adaptation of assistance systems; driver state detection.

DOI: 10.1504/IJVAS.2017.083515

International Journal of Vehicle Autonomous Systems, 2017 Vol.13 No.3, pp.244 - 260

Available online: 07 Apr 2017 *

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