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Towards Efficient Vehicle Dynamics Evaluation using Correlations of Objective Metrics and Subjective Assessments
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Vehicle Dynamics.
2015 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2015. , xiv, 64 p.
Series
TRITA-AVE, ISSN 1651-7660 ; 2015:28
National Category
Vehicle Engineering
Identifiers
URN: urn:nbn:se:kth:diva-169085OAI: oai:DiVA.org:kth-169085DiVA: diva2:819660
Presentation
2015-06-12, Vehicle Engineering Lab, Teknikringen 8, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20150611

Available from: 2015-06-11 Created: 2015-06-11 Last updated: 2015-06-11Bibliographically approved
List of papers
1. Correlations of subjective assessments and objective metrics for vehicle handling and steering: A walk through history
Open this publication in new window or tab >>Correlations of subjective assessments and objective metrics for vehicle handling and steering: A walk through history
2016 (English)In: International Journal of Vehicle Design, ISSN 0143-3369, E-ISSN 1741-5314, Vol. 72, no 1, 17-67 p.Article in journal (Refereed) Published
Abstract [en]

Achieving customer satisfaction concerning steering feel and vehicle handling requires subjective assessments and tuning of vehicle components by expert test drivers and engineers. Extensive subjective testing is expensive, time consuming and requires physical vehicles, which is in conflict with reduction of development time and cost. Objective testing and model-based development are constantly increasing but translating subjective requirements into objective ones is non-trivial. This paper summarises, discusses and classifies the methods, strategies and findings in previously published research regarding correlations of subjective assessments and objective metrics for vehicle handling and steering. The aim is twofold: (i) to identify key parameters of steering, handling and their preferred values and (ii) to compile and discuss the fundamental issues to deal with in the continued search for correlations between objective metrics and subjective assessments. The paper gives a comprehensive overview and insight of different aspects to take into account when conducting research in this field.

Place, publisher, year, edition, pages
Inderscience Enterprises, 2016
Keyword
steering feel, vehicle handling, driver preferences, objective metrics, subjective assessments, regression analysis, neural networks, fuzzy logic, vehicle steering, customer satisfaction, literature review
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering; SRA - Transport
Identifiers
urn:nbn:se:kth:diva-169081 (URN)10.1504/IJVD.2016.079191 (DOI)000391087600002 ()2-s2.0-84989221515 (Scopus ID)
Projects
iCOMSA
Funder
VINNOVA, 2012-04609
Note

QC 20170127

Available from: 2015-06-11 Created: 2015-06-11 Last updated: 2017-12-04Bibliographically approved
2. Findings from subjective evaluations and driver ratings of vehicle dynamics: steering and handling
Open this publication in new window or tab >>Findings from subjective evaluations and driver ratings of vehicle dynamics: steering and handling
2015 (English)In: Vehicle System Dynamics, ISSN 0042-3114, E-ISSN 1744-5159, Vol. 53, no 10, 1416-1438 p.Article in journal (Refereed) Published
Abstract [en]

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 predefined-driving 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.

Place, publisher, year, edition, pages
Taylor & Francis, 2015
Keyword
steering feel, vehicle handling, driver preference, subjective assessments, regression analysis
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-169082 (URN)10.1080/00423114.2015.1050402 (DOI)000375451500003 ()2-s2.0-84940607901 (Scopus ID)
Projects
iCOMSA
Funder
VINNOVA, 2012-04609
Note

QC 20170314

Available from: 2015-06-11 Created: 2015-06-11 Last updated: 2017-12-04Bibliographically approved
3. Objective metrics for vehicle handling and steering and their correlations with subjective assessments
Open this publication in new window or tab >>Objective metrics for vehicle handling and steering and their correlations with subjective assessments
2016 (English)In: International Journal of Automotive Technology, ISSN 1229-9138, E-ISSN 1976-3832, Vol. 17, no 5, 777-794 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Korean Society of Automotive Engineers, 2016
Keyword
Driver preference; Neural network; Objective metrics; Regression analysis; Steering feel; Subjective assessments; Vehicle handling
National Category
Vehicle Engineering
Identifiers
urn:nbn:se:kth:diva-169083 (URN)10.1007/s12239-016-0077-y (DOI)000379040800005 ()2-s2.0-84977119468 (Scopus ID)
Note

QC 20160819

Available from: 2015-06-11 Created: 2015-06-11 Last updated: 2017-12-04Bibliographically approved

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Licentiate Thesis(9616 kB)609 downloads
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