@article{ref1,
title="Processing driving simulator data before statistical analysis by means of interpolation and an integral formula",
journal="Transportmetrica A: transport science",
year="2024",
author="Wets, Geert and Brijs, Tom and Song, Yanchao and Ross, Veerle and Vanroelen, Giovanni and Brijs, Kris and Daniels, Stijn and Mollu, Kristof and Jongen, Ellen M.M. and Ariën, Caroline and Cornu, Joris",
volume="20",
number="3",
pages="e2179347-e2179347",
abstract="Driving simulator data can be sampled in function of distance (equally spaced) or time (with constant frequency). Consequently, the sampling data might have problems in the envisaged type of analysis (i.e. point location based analysis vs. zonal-based analysis). These issues are illustrated by means of five driving simulator datasets. The nearest sampled parameter value in the direct vicinity of the specific point is a very good proxy for the driving parameter value at the point of interest along the road. The analysis of driving parameters in zones requires a different approach. In summary, the interpolation technique is preferred over using raw sampled data to calculate mean parameter values. We introduce an equivalent time integral formula to compute the mean value of a driving parameter with respect to distance. Based on this paper, we demonstrate that it is very important to mention the data processing approach in driving simulator methodology.<p />",
language="en",
issn="2324-9935",
doi="10.1080/23249935.2023.2179347",
url="http://dx.doi.org/10.1080/23249935.2023.2179347"
}