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Effects of Driver Characteristics and Driver State on Predicting Turning Maneuvers in Urban Areas: Is There a Need for Individualized Parametrization?

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Advances in Human Aspects of Transportation

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 484))

Abstract

In future, advanced driver assistance systems (ADAS) may be able to adapt to the needs of the driver, thus reducing the risk of information overload in complex traffic situations. One way of achieving this may include the use of predictive algorithms that anticipate the driver’s intention to perform a certain traffic maneuver based on vehicle data, such as acceleration and deceleration parameters. In order to explore whether the predictive quality of such algorithms may be mitigated by individual driver-specific parameters such as driver characteristics (i.e. emotional driving [ED] and uncritical self-awareness [US]) as well as driver state (specifically stress), an empirical test-track study was conducted with N = 40 participants. The results indicate that maximum longitudinal and lateral acceleration vary significantly depending on driver characteristics. Moreover, analyses of the collected data suggest that incorporating psychological aspects into driver models can promote new insights into driving behavior.

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Acknowledgments

Research was conducted in the context of the project “Recognition of driver intention—prediction of driver behavior” as part of the German research initiative UR:BAN (http://urban-online.org). UR:BAN is supported by the German Federal Ministry of Economics and Technology on the basis of a decision by the German Bundestag.

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Authors and Affiliations

  1. Human Factors Institute, Universität der Bundeswehr München, Werner-Heisenberg-Weg 39, 85579, Neubiberg, Germany

    Matthias Graichen & Verena Nitsch

Authors
  1. Matthias Graichen
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  2. Verena Nitsch
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Corresponding author

Correspondence to Matthias Graichen .

Editor information

Editors and Affiliations

  1. Faculty of Engineering and the Environme, University of Southampton Faculty of Engineering and the Environme, Southampton, United Kingdom

    Neville A. Stanton

  2. Purdue University , West Lafayette, IN, USA

    Steven Landry

  3. Dipartimento di Architettura, Università degli Studi “G.d’Annunzio” Chiet, Pescara, Italy

    Giuseppe Di Bucchianico

  4. Dipartimento di Architettura, Università degli Studi “G.d’Annunzio” Chiet, Pescara, Italy

    Andrea Vallicelli

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Graichen, M., Nitsch, V. (2017). Effects of Driver Characteristics and Driver State on Predicting Turning Maneuvers in Urban Areas: Is There a Need for Individualized Parametrization?. In: Stanton, N., Landry, S., Di Bucchianico, G., Vallicelli, A. (eds) Advances in Human Aspects of Transportation. Advances in Intelligent Systems and Computing, vol 484. Springer, Cham. https://doi.org/10.1007/978-3-319-41682-3_2

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  • DOI: https://doi.org/10.1007/978-3-319-41682-3_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41681-6

  • Online ISBN: 978-3-319-41682-3

  • eBook Packages: EngineeringEngineering (R0)

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