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Objective metrics for vehicle handling and steering and their correlations with subjective assessments

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Abstract

This paper focuses on increasing the available knowledge about correlations between objective metrics and subjective assessments in steering feel and vehicle handling. Linear and non-linear correlations have been searched for by means of linear regression and neural network training, complemented by different statistical tools. For example, descriptive statistics, the t-distribution and the normal distribution have been used to define the 95% confidence interval for expected subjective assessments and their mean, which makes it possible to predict the subjective rating related to a given objective metric and its area of confidence. Single- and multi-driver correlations have been investigated, as well as how the use of different databases and different vehicle classes affects the results. A method for automatizing the search for correlations when using the driver-by-driver strategy is also explained and evaluated. Ranges of preferred objective metrics for vehicle dynamics have been defined. Vehicles with characteristics within these ranges of values are expected to receive a higher subjective rating when evaluated. Finally, linear correlations between objective metrics have been studied, linear dependency between objective metrics has been identified and its consequences have been presented.

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Abbreviations

2HN:

Two hidden neurons

Ay:

Lateral acceleration

DS:

Dataset (s)

DS1:

Dataset 1

DS2:

Dataset 2

DS3:

Dataset 3

GPS:

Global positioning system

LR:

Linear regression

MIMO:

Multiple input-multiple output

MSE:

Mean squared error

NN:

Neural network (s)

OM:

Objective metric (s)

R:

Regression coefficient

SA:

Subjective assessment (s)

SAC:

Straight-ahead controllability

SISO:

Single input-single output

SWA:

Steering wheel angle

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Correspondence to G. L. Gil Gómez.

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Gil Gómez, G.L., Nybacka, M., Bakker, E. et al. Objective metrics for vehicle handling and steering and their correlations with subjective assessments. Int.J Automot. Technol. 17, 777–794 (2016). https://doi.org/10.1007/s12239-016-0077-y

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  • DOI: https://doi.org/10.1007/s12239-016-0077-y

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