Links between subjective assessments and objective metrics for steering, and evaluation of driver ratings

Nybacka, Mikael; He, Xuxin; Su, Zhicheng; Drugge, Lars; Bakker, Egbert

doi:10.1080/00423114.2013.876503

Cited by 26 publications

(30 citation statements)

References 14 publications

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“…Good and bad performance configurations were required, even error states were included, in order to identify differences between desired and undesired vehicles and to recognise key factors affecting SA. The spread should be larger than in previous studies [1,2] and the complexity of the changes in the vehicles should be limited to off-the-shelf components, and to the feasible time of the experiments. In order to determine the configurations of the vehicles previous CAE simulations would have been desired, but they were not available, a matrix with configurations for the desired vehicle dynamics effects was therefore built, engineering judgement was used to determine which vehicle configuration would produce the expected results, for example, extreme high torque dead-band via high steering ratio plus high steering power assist, narrow tyres and low tyre pressure.…”

Section: Test Drivers and Test Vehiclesmentioning

confidence: 98%

“…In order to extend the amount of data available from previous studies, [1,2] a new series of test were conducted. The final database comprised 22 drivers and 51 vehicles, including C, D, E and SUV classes.…”

Section: Test Drivers and Test Vehiclesmentioning

confidence: 99%

“…However, this process would benefit from correlations between OM and SA, as they would allow better target selection and prediction of the expected SA from OM. [1][2][3][4] In the case of CAE OM, this would mean that the performance and driving feel of the vehicles could be optimised without the need for physical prototypes. MBDS permits SA of virtual vehicles, that is, test drivers can evaluate virtual vehicles before they even exist as real cars.…”

Section: Introductionmentioning

confidence: 99%

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Findings from subjective evaluations and driver ratings of vehicle dynamics: steering and handling

Gómez

Nybacka

Bakker

et al. 2015

Vehicle System Dynamics

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This paper investigates subjective assessments (SA) of vehicle handling and steering feel tests, both numerical and verbal, to understand drivers' use of judgement scales, rating tendencies and spread. Two different test methods are compared: a short multi-vehicle first-impression test with predefineddriving vs the standard extensive single-vehicle free-driving tests, both offering very similar results but with the former saving substantial testing time. Rating repeatability is evaluated by means of a blind test. Key SA questions are identified by numerical subjective assessment autocorrelations and by generating word clouds from the most used terms in verbal assessments, with both methods leading to similar key parameters. The results exposed in this paper enable better understanding of SA, allowing improving the overall subjective testing and evaluation process, and improving the data collection and analysis process needed before identifying correlations between SA and objective metrics.

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Section: Test Drivers and Test Vehiclesmentioning

confidence: 98%

Section: Test Drivers and Test Vehiclesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Findings from subjective evaluations and driver ratings of vehicle dynamics: steering and handling

Gómez

Nybacka

Bakker

et al. 2015

Vehicle System Dynamics

Self Cite

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“…Käppler et al (1992) based on a review of test procedures and scales, explained that test standards and scale deficiencies may lead to inadequate results. The SA questionnaire was therefore modified with respect to the one used for summer SA in previous research done by the authors (Nybacka et al 2014a, b, Gil Gómez et al 2015. The lesson learned in those studies was applied, as well as some modifications in order to study their effect on the SA, resulting in the SA questionnaire presented on Appendix A.…”

Section: Subjective Questionnairementioning

confidence: 99%

“…Although objective evaluations are well defined for high friction conditions, or summer testing, the correlations between objective metrics (OM) and SA are still under development (Chen & Crolla 1998, Harrer et al 2006, King et al 2002, Nybacka et al 2014a. Furthermore, these objective methods are not directly applicable for low friction testing, or winter testing, because the added challenge of constantly changing surface conditions.…”

mentioning

confidence: 99%

The importance of yaw motion feedback in driving simulators

Kusachov¹,

Bruzelius²,

Xie³

2016

The Dynamics of Vehicles on Roads and Tracks

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Currently the development and evaluation of winter vehicle handling characteristics are almost solely based on subjective assessments (SA) done by expert drivers. This is both expensive and time consuming, and therefore in conflict with the general goal of shortening project development and testing time meanwhile fulfilling more restrictive and demanding specifications.A more effective vehicle dynamics evaluation would be to use Computer Aided Engineering (CAE) for objective testing. Although objective evaluations are well defined for high friction conditions, or summer testing, the correlations between objective metrics (OM) and SA are still under development (Chen & Crolla 1998, Harrer et al. 2006, King et al. 2002, Nybacka et al. 2014a. Furthermore, these objective methods are not directly applicable for low friction testing, or winter testing, because the added challenge of constantly changing surface conditions. This causes both low signal-to-noise ratio measurements and low robustness, or repeatability, of the results. This difficult situation is increased by the fact that there is only one short winter test season per year and hemisphere, which limits the possibilities to shorten project times, as several winter test periods are normally required. All the above are motivations to understand: − How expert drivers perform their winter SA. − How objective tests, measurements and OM shall be defined for winter tests. − How OM and SA correlate in winter conditions and compares with summer conditions. During this research, a winter test expedition was performed in order to develop the methods to evaluate vehicle dynamics handling on winter conditions, see Figure 1. The goals of the performed tests were to study how winter objective testing should be performed when using steering robots. By identifying the suitability of different objective test manoeuvres, methods and/or procedures; the effects that the surface conditions have on the results and their repeatability, and if key OM are robust enough to describe the vehicle performance during changing surface ABSTRACT: This paper presents a test procedure developed to gather good quality data from objective and subjective testing on winter conditions. As the final goal of this test is to analyse the correlation between objective metrics and subjective assessments on winter for steering and handling, this procedure has to ensure a minimum change of the surface properties, which has a major influence on vehicle performance, during the whole test campaign. Therefore, the method presented keeps the total test time very low and allows similar vehicle configurations to be tested, objectively and subjectively, very close in time. Moreover, continuous maintenance work on the ice is performed. Reference vehicles are also used to monitor the changes on vehicle performance caused by weather conditions, which are inevitable. The method showed to be very effective. Initial results on objective metrics and subjective assessments are also presented.

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Formulating Engineering Systems Requirements

Zimmermann

Weck

2021

Handbook of Engineering Systems Design

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Links between subjective assessments and objective metrics for steering, and evaluation of driver ratings

Cited by 26 publications

References 14 publications

Findings from subjective evaluations and driver ratings of vehicle dynamics: steering and handling

Findings from subjective evaluations and driver ratings of vehicle dynamics: steering and handling

The importance of yaw motion feedback in driving simulators

Formulating Engineering Systems Requirements

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