Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Towards efficient vehicle dynamics development: From subjective assessments to objective metrics, from physical to virtual testing
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Vehicle Dynamics. Volvo Cars.ORCID iD: 0000-0002-6699-1965
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Vehicle dynamics development is strongly based on subjective assessments (SA) of vehicle prototypes, which is expensive and time consuming. Consequently, in the age of computer- aided engineering (CAE), there is a drive towards reducing this dependency on physical test- ing. However, computers are known for their remarkable processing capacity, not for their feelings. Therefore, before SA can be computed, it is required to properly understand the cor- relation between SA and objective metrics (OM), which can be calculated by simulations, and to understand how this knowledge can enable a more efficient and effective development process.

The approach to this research was firstly to identify key OM and SA in vehicle dynamics, based on the multicollinearity of OM and of SA, and on interviews with expert drivers. Sec- ondly, linear regressions and artificial neural network (ANN) were used to identify the ranges of preferred OM that lead to good SA-ratings. This result is the base for objective require- ments, a must in effective vehicle dynamics development and verification.

The main result of this doctoral thesis is the development of a method capable of predicting SA from combinations of key OM. Firstly, this method generates a classification map of ve- hicles solely based on their OM, which allows for a qualitative prediction of the steering feel of a new vehicle based on its position, and that of its neighbours, in the map. This prediction is enhanced with descriptive word-clouds, which summarizes in a few words the comments of expert test drivers to each vehicle in the map. Then, a second superimposed ANN displays the evolution of SA-ratings in the map, and therefore, allows one to forecast the SA-rating for the new vehicle. Moreover, this method has been used to analyse the effect of the tolerances of OM requirements, as well as to verify the previously identified preferred range of OM.

This thesis focused on OM-SA correlations in summer conditions, but it also aimed to in- crease the effectiveness of vehicle dynamics development in general. For winter conditions, where objective testing is not yet mature, this research initiates the definition and identifica- tion of robust objective manoeuvres and OM. Experimental data were used together with CAE optimisations and ANOVA-analysis to optimise the manoeuvres, which were verified in a second experiment. To improve the quality and efficiency of SA, Volvo’s Moving Base Driving Simulator (MBDS) was validated for vehicle dynamics SA-ratings. Furthermore, a tablet-app to aid vehicle dynamics SA was developed and validated.

Combined this research encompasses a comprehensive method for a more effective and ob- jective development process for vehicle dynamics. This has been done by increasing the un- derstanding of OM, SA and their relations, which enables more effective SA (key SA, MBDS, SA-app), facilitates objective requirements and therefore CAE development, identi- fies key OM and their preferred ranges, and which allow to predict SA solely based on OM. 

Place, publisher, year, edition, pages
Stockholm: Kungliga tekniska högskolan, 2017. , p. 72
Series
TRITA-AVE, ISSN 1651-7660 ; 2017:12
Keywords [en]
Steering feel, vehicle handling, driver preference, objective metrics, subjective assessments, regression analysis, artificial neural network
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
URN: urn:nbn:se:kth:diva-202348ISBN: 978-91-7729-302-6 (print)OAI: oai:DiVA.org:kth-202348DiVA, id: diva2:1075945
Public defence
2017-03-17, D3, Lindstedsvägen 5, Stockholm, 10:00 (English)
Opponent
Supervisors
Projects
iCOMSA
Funder
VINNOVA, 2012-04609
Note

QC 20170223

Available from: 2017-02-23 Created: 2017-02-21 Last updated: 2017-02-23Bibliographically 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, p. 17-67Article 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
Keywords
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, p. 1416-1438Article 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
Keywords
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, p. 777-794Article 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
Keywords
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
4. Machine learning to classify and predict objective and subjective assessments of vehicle dynamics: the case of steering feel.
Open this publication in new window or tab >>Machine learning to classify and predict objective and subjective assessments of vehicle dynamics: the case of steering feel.
2018 (English)In: Vehicle System Dynamics, ISSN 0042-3114, E-ISSN 1744-5159, Vol. 56, no 1, p. 150-171Article in journal (Refereed) Published
Abstract [en]

Objective measurements and computer-aided engineering simu- lations cannot be exploited to their full potential because of the high importance of driver feel in vehicle development. Further- more, despite many studies, it is not easy to identify the relation- ship between objective metrics (OM) and subjective assessments (SA), a task further complicated by the fact that SA change between drivers and geographical locations or with time. This paper presents a method which uses two artificial neural networks built on top of each other that helps to close this gap. The first network, based solely on OM, generates a map that groups together similar vehicles, thus allowing a classification of measured vehicles to be visualised. This map objectively demonstrates that there exist brand and vehi- cle class identities. It also foresees the subjective characteristics of a new vehicle, based on its requirements, simulations and measure- ments. These characteristics are described by the neighbourhood of the new vehicle in the map, which is made up of known vehicles that are accompanied by word-clouds that enhance this description. This forecast is also extended to perform a sensitivity analysis of the tolerances in the requirements, as well as to validate previously pub- lished preferred range of steering feel metrics. The results suggest a few new modifications. Finally, the qualitative information given by this measurement-based classification is complemented with a second superimposed network. This network describes a regression surface that enables quantitative predictions, for example the SA of the steering feel of a new vehicle from its OM. 

Place, publisher, year, edition, pages
Taylor & Francis Group, 2018
Keywords
Objective metrics, Driver preference, Subjective assessments, Neural network, Regression analysis, Steering feel, Vehicle dynamics.
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-202345 (URN)10.1080/00423114.2017.1351617 (DOI)000415982200008 ()2-s2.0-85025804899 (Scopus ID)
Projects
iCOMSA
Funder
VINNOVA, 2012-04609TrenOp, Transport Research Environment with Novel Perspectives
Note

QC 20170308

Available from: 2017-02-21 Created: 2017-02-21 Last updated: 2017-12-11Bibliographically approved
5. Analysing vehicle dynamics objective and subjective testing in winter conditions
Open this publication in new window or tab >>Analysing vehicle dynamics objective and subjective testing in winter conditions
2016 (English)In: The Dynamics of Vehicles on Roads and Tracks: Proceedings of the 24th Symposium of the International Association for Vehicle System Dynamics, IAVSD 2015, Taylor & Francis Group, 2016, p. 759-768Conference paper, Published paper (Refereed)
Abstract [en]

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 test- ed, 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 per- formance 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. 

Place, publisher, year, edition, pages
Taylor & Francis Group, 2016
Keywords
Subjective testing, System theory, Vehicles, Continuous maintenance, Objective metrics, Subjective assessments, Test campaign, Test procedures, Vehicle configuration, Vehicle dynamics, Winter conditions, Vehicle performance
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-181060 (URN)10.1201/b21185-81 (DOI)000385792300079 ()9781138028852 (ISBN)978-1-4987-7702-5 (ISBN)
Conference
24th Symposium of the International Association for Vehicle System Dynamics, IAVSD 2015, Graz, Austria, 17 August 2015 - 21 August 2015
Projects
iCOMSA
Funder
VINNOVA, 2012-04609TrenOp, Transport Research Environment with Novel Perspectives
Note

QC 20160404

Available from: 2016-01-27 Created: 2016-01-27 Last updated: 2017-05-03Bibliographically approved
6. Analysis and optimisation of objective vehicle dynamics testing in winter conditions
Open this publication in new window or tab >>Analysis and optimisation of objective vehicle dynamics testing in winter conditions
Show others...
2017 (English)In: Vehicle System Dynamics, ISSN 0042-3114, E-ISSN 1744-5159, Vol. 55, no 7, p. 945-969Article in journal (Refereed) Published
Abstract [en]

Objective testing of vehicle handling in winter conditions has not been implemented yet because of its low repeatability and its low signal-to-noise ratio. Enabling this testing, by identifying robust manoeuvres and metrics, was the aim of this study. This has been achieved by using both experimental data, gathered with steering-robot tests on ice, and simulation models of different complexities. Simple bicycle models with brush and MF-tyre models were built, both optimally parameterised against the experimental data. The brush model presented a better balance in complexity performance. This model was also implemented in a Kalman filter to reduce measurement noise; however, a simpler low-pass filter showed almost similar results at lower cost. A more advanced full vehicle model was built in VI-CarRealTime, based on kinematics and compliance data, damper measurements, and real tyre measurements in winter conditions. This model offered better results and was therefore chosen to optimise the initial manoeuvres through test design and simulations. A sensitivity analysis (ANOVA) of the experimental data allowed one to classify the robustness of the metrics. Finally, to validate the results, the proposed and the initial manoeuvres were tested back to back in a new winter campaign.

Place, publisher, year, edition, pages
Taylor & Francis, 2017
Keywords
Objective testing, vehicle handling, vehicle modelling, winter conditions, winter test, signal processing, Kalman filter
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-201022 (URN)10.1080/00423114.2016.1278248 (DOI)000399659300001 ()2-s2.0-85009775094 (Scopus ID)
Projects
iCOMSA
Funder
VINNOVA, 2012-04609
Note

QC 20170208

Available from: 2017-02-07 Created: 2017-02-07 Last updated: 2017-06-07Bibliographically approved
7. Validation of a Moving Base Driving Simulator for Subjective Assessments of Steering Feel and Handling
Open this publication in new window or tab >>Validation of a Moving Base Driving Simulator for Subjective Assessments of Steering Feel and Handling
Show others...
2017 (English)In: 13th International Symposium on Advanced Vehicle Control, CRC Press/Balkema , 2017Conference paper, Published paper (Refereed)
Abstract [en]

Moving Base Driving Simulators (MBDS) have a large potential to increase effectiveness in vehicle dynamics development. MBDS can reduce dependency on vehicle-prototypes by allowing subjective assessments (SA) of models. Little is, however, known about the relation of SA in MBDS and in physical ve- hicles. This paper aims to increase this knowledge, and proposes and implements a methodology to validate MBDS for SA of steering feel and handling. Firstly, vehicle models were generated from Kinematics & Com- pliance measurements of real vehicles. These models were validated versus objective tests, with steering ro- bots, of the physical vehicles. These vehicles and their MBDS-models were assessed by expert drivers, using a scanned-test track in the MBDS. Comparison of the SA in both environments enabled the MBDS validation. Promising results, with higher SA accuracy for handling than for steering feel, indicates that the major im- provement effort should focus on the steering model and its simulation in the MBDS.

Place, publisher, year, edition, pages
CRC Press/Balkema, 2017
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-201023 (URN)2-s2.0-85017003596 (Scopus ID)9781315265285 (ISBN)
Conference
13th International Symposium on Advanced Vehicle Control, AVEC 2016; Munich; Germany; 13 September 2016 through 16 September 2016
Projects
iCOMSA
Funder
VINNOVA, 2012-04609
Note

QC 20170519

Available from: 2017-02-07 Created: 2017-02-07 Last updated: 2017-05-19Bibliographically approved
8. Improving subjective assessments of vehicle dynamics evaluations by means of computer tablets as digital aid
Open this publication in new window or tab >>Improving subjective assessments of vehicle dynamics evaluations by means of computer tablets as digital aid
Show others...
2016 (English)In: Computer software and hardware: Vehicle dynamics, SAE International , 2016Conference paper, Published paper (Refereed)
Abstract [en]

Vehicle dynamics development relies on subjective assessments (SA), which is a resource-intensive procedure requiring both expert drivers and vehicles. Furthermore, development projects becoming shorter and more complex, and increasing demands on quality require higher efficiency.

Most research in this area has focused on moving from physical to virtual testing. However, SA remains the central method. Less attention has been given to provide better tools for the SA process itself. One promising approach is to introduce computer-tablets to aid data collection, which has proven to be useful in medical studies. Simple software solutions can eliminate the need to transcribe data and generate more flexible and better maintainable questionnaires. Tablets’ technical features envision promising enhancements of SA, which also enable better correlations to objective metrics, a requirement to improve CAE evaluations.

However, it cannot be assumed that a tablet-based solution is feasible in vehicle dynamics SA context. Any distraction might result in low SA quality and safety issues when test-drivers are subjected to high mental workload pushing the vehicles to their performance-limits.

In this study, a SA tablet-software for steering feel, handling, and ride was developed and systematically evaluated versus the traditional pen-and-paper method. The results indicate that the new approach is technically feasible in this context, meets more use-cases, and the drivers’ attitude towards it is positive. It increased questionnaire completion and rating resolution while reducing the error rate and transcription time.

Although attendees reported that the paper-based approach has advantages from a usability point of view, the benefits of the tablet-based approach enable further process-related advantages.

Place, publisher, year, edition, pages
SAE International, 2016
Series
SAE Technical Paper ; 2016-01-1629
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-201031 (URN)10.4271/2016-01-1629 (DOI)2-s2.0-84975299989 (Scopus ID)
Conference
SAE 2016 World Congress and Exhibition
Projects
iCOMSA
Funder
VINNOVA, 2012-04609
Note

QC 20170208

Available from: 2017-02-08 Created: 2017-02-08 Last updated: 2017-02-21Bibliographically approved

Open Access in DiVA

fulltext(27055 kB)521 downloads
File information
File name FULLTEXT01.pdfFile size 27055 kBChecksum SHA-512
97c12ec1903543569b73ab1766e64a8f641550cc677fe832e7e9a0d687ecfd577c72861130e184b9f31ba690c64085b7be5a4599abe888d89dfdc5b0ee7593a9
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Gil Gómez, Gaspar
By organisation
Vehicle Dynamics
Vehicle Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 521 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 3267 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf