Application of Optimal Control Method to Path Tracking Problem of Vehicle
Path tracking is an essential stage for vehicle safety control. The study proposes an optimal control method for path tracking problem. Firstly, a nonlinear 4-DOF vehicle model is established. Secondly, the path optimization problem of vehicle is transformed into a nonlinear programming problem(NLP)...
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| Veröffentlicht in: | IEEE access 2024-01, Vol.12, p.1-1 |
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| creator | Liu, Yingjie Wang, Enhao |
| description | Path tracking is an essential stage for vehicle safety control. The study proposes an optimal control method for path tracking problem. Firstly, a nonlinear 4-DOF vehicle model is established. Secondly, the path optimization problem of vehicle is transformed into a nonlinear programming problem(NLP) by discretizing both control variables and state variables using the local collocation method. Then, in order to improve the efficiency of solving the NLP, an efficient calculation method for partial derivatives is established. Finally, a real vehicle test is executed to verify the rationality of the proposed model and methodology. The results show that by decomposing the partial derivative of the NLP into the partial derivative of the original path optimization problem the computational complexity of the first order partial derivative of NLP is significantly reduced improving computational efficiency even more significantly. |
| doi_str_mv | 10.1109/ACCESS.2024.3515081 |
| format | Article |
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The study proposes an optimal control method for path tracking problem. Firstly, a nonlinear 4-DOF vehicle model is established. Secondly, the path optimization problem of vehicle is transformed into a nonlinear programming problem(NLP) by discretizing both control variables and state variables using the local collocation method. Then, in order to improve the efficiency of solving the NLP, an efficient calculation method for partial derivatives is established. Finally, a real vehicle test is executed to verify the rationality of the proposed model and methodology. The results show that by decomposing the partial derivative of the NLP into the partial derivative of the original path optimization problem the computational complexity of the first order partial derivative of NLP is significantly reduced improving computational efficiency even more significantly.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2024.3515081</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>IEEE</publisher><subject>Accuracy ; Autonomous vehicles ; Computational efficiency ; Computational modeling ; Optimal control ; Path planning ; path tracking ; Planning ; Real-time systems ; symplectic pseudospectral method ; Target tracking ; Vehicle dynamics</subject><ispartof>IEEE access, 2024-01, Vol.12, p.1-1</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c261t-441b52f06de75047cac1d7aa24975ff66f7042faee3e4cee94f8a35d898a131a3</cites><orcidid>0000-0001-8615-7372 ; 0009-0007-2081-7922</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10802908$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,860,2096,27610,27901,27902,54908</link.rule.ids></links><search><creatorcontrib>Liu, Yingjie</creatorcontrib><creatorcontrib>Wang, Enhao</creatorcontrib><title>Application of Optimal Control Method to Path Tracking Problem of Vehicle</title><title>IEEE access</title><addtitle>Access</addtitle><description>Path tracking is an essential stage for vehicle safety control. The study proposes an optimal control method for path tracking problem. Firstly, a nonlinear 4-DOF vehicle model is established. Secondly, the path optimization problem of vehicle is transformed into a nonlinear programming problem(NLP) by discretizing both control variables and state variables using the local collocation method. Then, in order to improve the efficiency of solving the NLP, an efficient calculation method for partial derivatives is established. Finally, a real vehicle test is executed to verify the rationality of the proposed model and methodology. The results show that by decomposing the partial derivative of the NLP into the partial derivative of the original path optimization problem the computational complexity of the first order partial derivative of NLP is significantly reduced improving computational efficiency even more significantly.</description><subject>Accuracy</subject><subject>Autonomous vehicles</subject><subject>Computational efficiency</subject><subject>Computational modeling</subject><subject>Optimal control</subject><subject>Path planning</subject><subject>path tracking</subject><subject>Planning</subject><subject>Real-time systems</subject><subject>symplectic pseudospectral method</subject><subject>Target tracking</subject><subject>Vehicle dynamics</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNkN1Kw0AQRhdRsNQ-gV7sC6Tub7K5LKFqodJCq7fLdDPbpqbdssmNb29iRDo3M3xwDsNHyCNnU85Z_jwrivlmMxVMqKnUXDPDb8hI8DRPpJbp7dV9TyZNc2TdmC7S2YgsZpdLXTloq3CmwdPVpa1OUNMinNsYavqO7SGUtA10De2BbiO4r-q8p-sYdjWeeuQTD5Wr8YHceagbnPztMfl4mW-Lt2S5el0Us2XiRMrbRCm-08KztMRMM5U5cLzMAITKM-19mvqMKeEBUaJyiLnyBqQuTW6ASw5yTBaDtwxwtJfYvRu_bYDK_gYh7i3Etv_IcoPokGmvd04Zg2BUljouuMlVaYTvXHJwuRiaJqL_93Fm-3LtUK7ty7V_5XbU00BViHhFGCZyZuQPoSp1gw</recordid><startdate>20240101</startdate><enddate>20240101</enddate><creator>Liu, Yingjie</creator><creator>Wang, Enhao</creator><general>IEEE</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-8615-7372</orcidid><orcidid>https://orcid.org/0009-0007-2081-7922</orcidid></search><sort><creationdate>20240101</creationdate><title>Application of Optimal Control Method to Path Tracking Problem of Vehicle</title><author>Liu, Yingjie ; Wang, Enhao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c261t-441b52f06de75047cac1d7aa24975ff66f7042faee3e4cee94f8a35d898a131a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Accuracy</topic><topic>Autonomous vehicles</topic><topic>Computational efficiency</topic><topic>Computational modeling</topic><topic>Optimal control</topic><topic>Path planning</topic><topic>path tracking</topic><topic>Planning</topic><topic>Real-time systems</topic><topic>symplectic pseudospectral method</topic><topic>Target tracking</topic><topic>Vehicle dynamics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Yingjie</creatorcontrib><creatorcontrib>Wang, Enhao</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Xplore Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Xplore</collection><collection>CrossRef</collection><collection>Directory of Open Access Journals</collection><jtitle>IEEE access</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Yingjie</au><au>Wang, Enhao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of Optimal Control Method to Path Tracking Problem of Vehicle</atitle><jtitle>IEEE access</jtitle><stitle>Access</stitle><date>2024-01-01</date><risdate>2024</risdate><volume>12</volume><spage>1</spage><epage>1</epage><pages>1-1</pages><issn>2169-3536</issn><eissn>2169-3536</eissn><coden>IAECCG</coden><abstract>Path tracking is an essential stage for vehicle safety control. The study proposes an optimal control method for path tracking problem. Firstly, a nonlinear 4-DOF vehicle model is established. Secondly, the path optimization problem of vehicle is transformed into a nonlinear programming problem(NLP) by discretizing both control variables and state variables using the local collocation method. Then, in order to improve the efficiency of solving the NLP, an efficient calculation method for partial derivatives is established. Finally, a real vehicle test is executed to verify the rationality of the proposed model and methodology. 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| source | Directory of Open Access Journals; IEEE Xplore Open Access Journals; EZB Electronic Journals Library |
| subjects | Accuracy Autonomous vehicles Computational efficiency Computational modeling Optimal control Path planning path tracking Planning Real-time systems symplectic pseudospectral method Target tracking Vehicle dynamics |
| title | Application of Optimal Control Method to Path Tracking Problem of Vehicle |
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