Using mobile devices for driving test assessment

a study of acceleration and GPS data

Journal article (2024)

Authors

T. Driessen Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
David Stefan CBR Centraal Bureau Rijvaardigheid
Daniël Heikoop CBR Centraal Bureau Rijvaardigheid
D Dodou Medical Instruments & Bio-Inspired Technology - Mechanical, Maritime and Materials Engineering
D. Dodou Medical Instruments & Bio-Inspired Technology - Mechanical, Maritime and Materials Engineering
Dimitra Dodou Medical Instruments & Bio-Inspired Technology - Mechanical, Maritime and Materials Engineering
J.C.F. de Winter Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
J. C.F. de Winter Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
Research Group
Human-Robot Interaction (Mechanical, Maritime and Materials Engineering) (TU Delft)
More Info
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Published Date

2024

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Human-Robot Interaction

Abstract

There is a need to improve the validity of the driving test as a measure of an individual’s ability to drive safely. This paper explores the use of algorithms to analyze acceleration and GPS data from a smartphone and a GoPro to distinguish between different driving styles, as performed by experienced examiners portraying stereotypical driving test candidates. Measures from nine driving tests were analyzed, including (harsh) accelerations, jerk, mean speed, and speeding. Results showed that the type of car, instructed driving style, and driving route impacted the dependent measures. It is concluded that GPS and accelerometer data can effectively distinguish between cautious, normal, and aggressive driving. However, it is important to consider additional sensors, such as cameras, to allow for more context-aware assessments of driving behavior. Furthermore, we demonstrate methods to quantify variations in road conditions and provide suggestions for presenting the data to driving examiners.