Abstract
Advanced driver assistance systems (ADAS) can help to reduce road accidents. In order to increase the positive effects of these systems the warnings and interventions have to be adjusted to the driver’s behaviour. With regard to the human behaviour a real time capable algorithm for predicting driver’s manoeuvres was developed.
The basis for development of the algorithm were two controlled field studies with the focus on inter- and intraindividual behaviour in urban traffic situations. The algorithm is based on Fuzzy Logic and Edit Distance; it was trained with the data containing the driver’s behaviour before and during driving manoeuvres of the field study. Focus lies on the driver’s vehicle control and his head- and gaze behaviour. The feature selection was performed on the basis of true and false positives, false negatives and the prediction time horizon. The algorithm learns behavioural sequences of considered features in an offline training step and compares the actual driver’s behaviour with the trained sequences during the real-time detection to calculate the manoeuvre probability and the time horizon until a certain manoeuvre will be conducted.
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Heine, J., Langer, I., Schramm, T. (2018). Human Focused Development of a Manoeuvre Prediction in Urban Traffic Situations Based on Behavioural Sequences. In: Bengler, K., Drüke, J., Hoffmann, S., Manstetten, D., Neukum, A. (eds) UR:BAN Human Factors in Traffic. ATZ/MTZ-Fachbuch. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-15418-9_13
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