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Impact of Human-Centered Vestibular System Model for Motion Control in a Driving Simulator
This study presents a driving simulator experiment to evaluate three different motion cueing algorithms based on model predictive control. The difference among these motion strategies lies in the type of mathematical model used. The first one contains only the dynamic model of the platform, while th...
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Published in: | IEEE transactions on human-machine systems 2021-10, Vol.51 (5), p.411-420 |
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description | This study presents a driving simulator experiment to evaluate three different motion cueing algorithms based on model predictive control. The difference among these motion strategies lies in the type of mathematical model used. The first one contains only the dynamic model of the platform, while the others integrate additionally two different vestibular system models. We compare these three strategies to discuss the tradeoffs when including a vestibular system model in the control loop from the user's viewpoint. The study is conducted in autonomous mode and in free driving mode, as both play an important role in motion cueing validation. A total of 38 individuals participated in the experiment; 19 drove the simulator in free driving mode and the remaining using the autonomous driving mode. For both driving modes, substantial differences is observed. The analysis shows that one of the vestibular system models is suitable for driving simulators, as it thoroughly restores high-frequency accelerations and is well noted by the participants, especially those in the free driving mode. Further tests are needed to analyze the advantages of integrating the chosen vestibular system model in the control design for motion cuieng algorithms. Regarding the autonomous mode, further research is needed to examine the influence of the vestibular system model on the motion performance, as the behavior of the autonomous model may implicitly interfere with subjective assessments. |
doi_str_mv | 10.1109/THMS.2021.3102506 |
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The difference among these motion strategies lies in the type of mathematical model used. The first one contains only the dynamic model of the platform, while the others integrate additionally two different vestibular system models. We compare these three strategies to discuss the tradeoffs when including a vestibular system model in the control loop from the user's viewpoint. The study is conducted in autonomous mode and in free driving mode, as both play an important role in motion cueing validation. A total of 38 individuals participated in the experiment; 19 drove the simulator in free driving mode and the remaining using the autonomous driving mode. For both driving modes, substantial differences is observed. The analysis shows that one of the vestibular system models is suitable for driving simulators, as it thoroughly restores high-frequency accelerations and is well noted by the participants, especially those in the free driving mode. Further tests are needed to analyze the advantages of integrating the chosen vestibular system model in the control design for motion cuieng algorithms. Regarding the autonomous mode, further research is needed to examine the influence of the vestibular system model on the motion performance, as the behavior of the autonomous model may implicitly interfere with subjective assessments.</description><identifier>ISSN: 2168-2291</identifier><identifier>EISSN: 2168-2305</identifier><identifier>DOI: 10.1109/THMS.2021.3102506</identifier><identifier>CODEN: ITHSA6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Automatic ; Autonomous driving (AD) ; Computer Science ; Control design ; Control systems ; driving simulators (DSs) ; Dynamic models ; Engineering Sciences ; Force ; Human motion ; human motion perception ; Human-Computer Interaction ; Irrigation ; Mathematical model ; model predictive control (MPC) ; Modeling and Simulation ; Motion control ; motion cueing algorithms ; Predictive control ; Simulation ; Simulators ; Stability analysis ; Tuning ; Vehicle dynamics</subject><ispartof>IEEE transactions on human-machine systems, 2021-10, Vol.51 (5), p.411-420</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c370t-be535922f0f688c9eada8ca6d4a14805799e68e3eb6c744514bb67a974e5cbf33</citedby><cites>FETCH-LOGICAL-c370t-be535922f0f688c9eada8ca6d4a14805799e68e3eb6c744514bb67a974e5cbf33</cites><orcidid>0000-0002-1670-0584 ; 0000-0002-8926-1359</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9528891$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>230,314,780,784,885,27924,27925,54796</link.rule.ids><backlink>$$Uhttps://hal.science/hal-03366349$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Rengifo, Carolina</creatorcontrib><creatorcontrib>Chardonnet, Jean-Remy</creatorcontrib><creatorcontrib>Mohellebi, Hakim</creatorcontrib><creatorcontrib>Kemeny, Andras</creatorcontrib><title>Impact of Human-Centered Vestibular System Model for Motion Control in a Driving Simulator</title><title>IEEE transactions on human-machine systems</title><addtitle>THMS</addtitle><description>This study presents a driving simulator experiment to evaluate three different motion cueing algorithms based on model predictive control. The difference among these motion strategies lies in the type of mathematical model used. The first one contains only the dynamic model of the platform, while the others integrate additionally two different vestibular system models. We compare these three strategies to discuss the tradeoffs when including a vestibular system model in the control loop from the user's viewpoint. The study is conducted in autonomous mode and in free driving mode, as both play an important role in motion cueing validation. A total of 38 individuals participated in the experiment; 19 drove the simulator in free driving mode and the remaining using the autonomous driving mode. For both driving modes, substantial differences is observed. The analysis shows that one of the vestibular system models is suitable for driving simulators, as it thoroughly restores high-frequency accelerations and is well noted by the participants, especially those in the free driving mode. Further tests are needed to analyze the advantages of integrating the chosen vestibular system model in the control design for motion cuieng algorithms. Regarding the autonomous mode, further research is needed to examine the influence of the vestibular system model on the motion performance, as the behavior of the autonomous model may implicitly interfere with subjective assessments.</description><subject>Algorithms</subject><subject>Automatic</subject><subject>Autonomous driving (AD)</subject><subject>Computer Science</subject><subject>Control design</subject><subject>Control systems</subject><subject>driving simulators (DSs)</subject><subject>Dynamic models</subject><subject>Engineering Sciences</subject><subject>Force</subject><subject>Human motion</subject><subject>human motion perception</subject><subject>Human-Computer Interaction</subject><subject>Irrigation</subject><subject>Mathematical model</subject><subject>model predictive control (MPC)</subject><subject>Modeling and Simulation</subject><subject>Motion control</subject><subject>motion cueing algorithms</subject><subject>Predictive control</subject><subject>Simulation</subject><subject>Simulators</subject><subject>Stability analysis</subject><subject>Tuning</subject><subject>Vehicle dynamics</subject><issn>2168-2291</issn><issn>2168-2305</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNo9kE1Lw0AQhoMoWLQ_QLwsePKQuh_Zze6x1I8UWjy0evCybJKJbkmydZMU-u9NSO1cZhie92XmDYI7gmeEYPW0TdabGcWUzBjBlGNxEUwoETKkDPPL_5kqch1Mm2aH-5KUcy4nwdey2pusRa5ASVeZOlxA3YKHHH1C09q0K41Hm2PTQoXWLocSFc73U2tdjRaubr0rka2RQc_eHmz9jTa26kWt87fBVWHKBqanfhN8vL5sF0m4en9bLuarMGMxbsMUOOOK0gIXQspMgcmNzIzII0MiiXmsFAgJDFKRxVHESZSmIjYqjoBnacHYTfA4-v6YUu-9rYw_amesTuYrPewwY0KwSB1Izz6M7N67367_UO9c5-v-PE15zHiMOVE9RUYq865pPBRnW4L1kLgeEtdD4vqUeK-5HzUWAM684lRKRdgf14d7Ig</recordid><startdate>202110</startdate><enddate>202110</enddate><creator>Rengifo, Carolina</creator><creator>Chardonnet, Jean-Remy</creator><creator>Mohellebi, Hakim</creator><creator>Kemeny, Andras</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0002-1670-0584</orcidid><orcidid>https://orcid.org/0000-0002-8926-1359</orcidid></search><sort><creationdate>202110</creationdate><title>Impact of Human-Centered Vestibular System Model for Motion Control in a Driving Simulator</title><author>Rengifo, Carolina ; Chardonnet, Jean-Remy ; Mohellebi, Hakim ; Kemeny, Andras</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c370t-be535922f0f688c9eada8ca6d4a14805799e68e3eb6c744514bb67a974e5cbf33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Automatic</topic><topic>Autonomous driving (AD)</topic><topic>Computer Science</topic><topic>Control design</topic><topic>Control systems</topic><topic>driving simulators (DSs)</topic><topic>Dynamic models</topic><topic>Engineering Sciences</topic><topic>Force</topic><topic>Human motion</topic><topic>human motion perception</topic><topic>Human-Computer Interaction</topic><topic>Irrigation</topic><topic>Mathematical model</topic><topic>model predictive control (MPC)</topic><topic>Modeling and Simulation</topic><topic>Motion control</topic><topic>motion cueing algorithms</topic><topic>Predictive control</topic><topic>Simulation</topic><topic>Simulators</topic><topic>Stability analysis</topic><topic>Tuning</topic><topic>Vehicle dynamics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rengifo, Carolina</creatorcontrib><creatorcontrib>Chardonnet, Jean-Remy</creatorcontrib><creatorcontrib>Mohellebi, Hakim</creatorcontrib><creatorcontrib>Kemeny, Andras</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>IEEE transactions on human-machine systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rengifo, Carolina</au><au>Chardonnet, Jean-Remy</au><au>Mohellebi, Hakim</au><au>Kemeny, Andras</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Impact of Human-Centered Vestibular System Model for Motion Control in a Driving Simulator</atitle><jtitle>IEEE transactions on human-machine systems</jtitle><stitle>THMS</stitle><date>2021-10</date><risdate>2021</risdate><volume>51</volume><issue>5</issue><spage>411</spage><epage>420</epage><pages>411-420</pages><issn>2168-2291</issn><eissn>2168-2305</eissn><coden>ITHSA6</coden><abstract>This study presents a driving simulator experiment to evaluate three different motion cueing algorithms based on model predictive control. The difference among these motion strategies lies in the type of mathematical model used. The first one contains only the dynamic model of the platform, while the others integrate additionally two different vestibular system models. We compare these three strategies to discuss the tradeoffs when including a vestibular system model in the control loop from the user's viewpoint. The study is conducted in autonomous mode and in free driving mode, as both play an important role in motion cueing validation. A total of 38 individuals participated in the experiment; 19 drove the simulator in free driving mode and the remaining using the autonomous driving mode. For both driving modes, substantial differences is observed. The analysis shows that one of the vestibular system models is suitable for driving simulators, as it thoroughly restores high-frequency accelerations and is well noted by the participants, especially those in the free driving mode. Further tests are needed to analyze the advantages of integrating the chosen vestibular system model in the control design for motion cuieng algorithms. Regarding the autonomous mode, further research is needed to examine the influence of the vestibular system model on the motion performance, as the behavior of the autonomous model may implicitly interfere with subjective assessments.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/THMS.2021.3102506</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-1670-0584</orcidid><orcidid>https://orcid.org/0000-0002-8926-1359</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Automatic Autonomous driving (AD) Computer Science Control design Control systems driving simulators (DSs) Dynamic models Engineering Sciences Force Human motion human motion perception Human-Computer Interaction Irrigation Mathematical model model predictive control (MPC) Modeling and Simulation Motion control motion cueing algorithms Predictive control Simulation Simulators Stability analysis Tuning Vehicle dynamics |
title | Impact of Human-Centered Vestibular System Model for Motion Control in a Driving Simulator |
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