UR:BAN Human Factors in Traffic pp 163-182

Part of the ATZ/MTZ-Fachbuch book series (ATZMTZ) | Cite as

Analysing Behavioural Data from On-Road Driving Studies: Handling the Challenges of Data Processing

  • Matthias Graichen
  • Verena Nitsch
  • Berthold Färber
Chapter

Abstract

The analysis of real world driving data entails numerous challenges. In this chapter, several strategies are proposed to meet challenges that surface in data storage, data extraction, data correction and data enrichment. The strategies are illustrated with examples from a study that had been conducted as part of the UR:BAN research project ”Behaviour Prediction and Intention Detection” (VIE), which aimed at investigating driving behaviour when approaching intersections under real environmental conditions in order to predict turning manoeuvres at urban intersections. It was demonstrated that with the proposed data infrastructure, correction procedures and extracted filters for potentially confounding variables, it is possible to establish a “clean” data basis to implement and adjust a prediction algorithm for turning manoeuvres according to individual driver characteristics.

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Copyright information

© Springer Fachmedien Wiesbaden GmbH 2018

Authors and Affiliations

  • Matthias Graichen
    • 1
  • Verena Nitsch
    • 1
  • Berthold Färber
    • 1
  1. 1.Human Factors InstituteUniversität der Bundeswehr MünchenNeubibergGermany

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