Reading: The Driver Experience Under Extreme Lane Change Conditions


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Research Article

The Driver Experience Under Extreme Lane Change Conditions


Joop Pauwelussen

HAN University of Applied Sciences, NL
About Joop
Professor in Mobility Technology
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The objective of this paper is to examine the driver’s mental workload experience during extreme nonlinear high slip driving conditions, i.e. with the tyres being close to saturation. This is done for the ISO Double Lane Change manoeuvre, based on extensive test data from two professional test drivers, for different speeds, and with varying tyres. Optimal double lane change closed loop performance is defined and determined and compared to the actual test performance, showing and explaining differences in this performance. A path-tracking driver model has been applied to examine the driver model parameters steering gain and preview time. It is shown that these parameters, which can easily be derived from the closed loop vehicle handling data, vary with mental workload as experienced by these test drivers. This correlation has been demonstrated in previous research for normal driving conditions, where workload, in this paper determined through RSME (Rating Scale Mental Effort) scores, is affected by traffic conditions, where fatigue, experience and learning effects play a significant role. Hence, this paper shows that this, i.e. using the driver model as a virtual sensor to estimate mental workload, can be extended to high slip conditions.

Driver model parameters vary in time, and are not independent. Different combinations of preview time and steering gain lead to the same closed loop performance. We have extended the application of the driver model, the relationship between the driver model parameters and closed loop stability to high slip conditions, before we applied it to severe, i.e. high slip lane change performance.

How to Cite: Pauwelussen, J., 2018. The Driver Experience Under Extreme Lane Change Conditions. International Journal of Driving Science, 1(1), p.1. DOI:
  Published on 26 Nov 2018

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