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The Research Initiative UR:BAN Read chapter Read first chapter

2018 | OriginalPaper | Chapter

12. Fusion of Driver Behaviour Analysis and Situation Assessment for Probabilistic Driving Manoeuvre Prediction

Authors : Veit Leonhardt, Timo Pech, Prof. Dr. Gerd Wanielik

Published in: UR:BAN Human Factors in Traffic

Publisher: Springer Fachmedien Wiesbaden

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Abstract

The task of driving is very complex and highly demanding for the individual. The optimal driver assistance strongly depends on the situation and the driver’s needs. In particular, this applies to driving manoeuvres as lane changes. Consequently, future advanced driver assistance systems will have to detect and assess driving situations as well as the driver’s intentions automatically before a driving manoeuvre is initiated.
The method proposed predicts situations of upcoming lane changes based on assessments of the environmental situation and the driver’s behaviour. For this purpose, information gained from a 360° sensory perception of the vehicle surroundings and from the analysis of the driver’s gaze behaviour is fused by means of a Bayesian network. The implemented algorithms work in real-time and provide a probabilistic estimation of the intention of the driver to perform a specific manoeuvre. The application of prediction was integrated into a test vehicle and evaluated by using real traffic data and driving studies.

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previous chapter Lane Change Prediction: From Driver Characteristics, Manoeuvre Types and Glance Behaviour to a Real-Time Prediction Algorithm
next chapter Human Focused Development of a Manoeuvre Prediction in Urban Traffic Situations Based on Behavioural Sequences
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Metadata
Title
Fusion of Driver Behaviour Analysis and Situation Assessment for Probabilistic Driving Manoeuvre Prediction
Authors
Veit Leonhardt
Timo Pech
Prof. Dr. Gerd Wanielik
Copyright Year
2018
Publisher
Springer Fachmedien Wiesbaden
Book
UR:BAN Human Factors in Traffic

Print ISBN: 978-3-658-15417-2

Electronic ISBN: 978-3-658-15418-9

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-658-15418-9_12

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