Hitch Angle Estimation of a Towing Vehicle With Arbitrary Configuration
In this paper, ultra-sonic sensors along with kinematics and dynamics equations of a towing vehicle are used to develop three approaches for hitch angle estimation. The first approach is based on direct calculation of hitch angle using certain a priori geometric information and distance measurements...
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Veröffentlicht in: | IEEE transactions on intelligent transportation systems 2022-07, Vol.23 (7), p.7535-7546 |
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creator | Habibnejad Korayem, Amin Pazooki, Alireza Durali, Laleh Khajepour, Amir Fidan, Baris Ponnuswami, Anushya Viraliur Khaligh, Sepehr Pourrezaei |
description | In this paper, ultra-sonic sensors along with kinematics and dynamics equations of a towing vehicle are used to develop three approaches for hitch angle estimation. The first approach is based on direct calculation of hitch angle using certain a priori geometric information and distance measurements of four ultra-sonic sensors. An angle estimate is generated for each of the six possible sensor-pair combinations, and these six estimates are passed through a voting algorithm to produce a single estimate. As the second and third approaches, kinematic and dynamic models of the tractor-trailer system are used to develop least-squares and Kalman filtering based recursive hitch angle estimations. A more reliable hitch angle estimation scheme is then proposed as the integration of the algorithms developed following each of the three approaches via a switching data fusion logic. It is shown that the proposed integrated hitch angle estimation scheme can be used for any ball type box trailer with a flat or symmetric V-nose frontal face without any priori information on the trailer parameters. Based on the validity of the assumptions, the proposed scheme can estimate the hitch angle in both low-speed using the kinematic model, and high-speed using the dynamic model of the tractor-trailer system. Experimental results corroborate the algorithms in estimating the hitch angle estimates in various cases conducted in this study. |
doi_str_mv | 10.1109/TITS.2021.3071391 |
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The first approach is based on direct calculation of hitch angle using certain a priori geometric information and distance measurements of four ultra-sonic sensors. An angle estimate is generated for each of the six possible sensor-pair combinations, and these six estimates are passed through a voting algorithm to produce a single estimate. As the second and third approaches, kinematic and dynamic models of the tractor-trailer system are used to develop least-squares and Kalman filtering based recursive hitch angle estimations. A more reliable hitch angle estimation scheme is then proposed as the integration of the algorithms developed following each of the three approaches via a switching data fusion logic. It is shown that the proposed integrated hitch angle estimation scheme can be used for any ball type box trailer with a flat or symmetric V-nose frontal face without any priori information on the trailer parameters. Based on the validity of the assumptions, the proposed scheme can estimate the hitch angle in both low-speed using the kinematic model, and high-speed using the dynamic model of the tractor-trailer system. Experimental results corroborate the algorithms in estimating the hitch angle estimates in various cases conducted in this study.</description><identifier>ISSN: 1524-9050</identifier><identifier>EISSN: 1558-0016</identifier><identifier>DOI: 10.1109/TITS.2021.3071391</identifier><identifier>CODEN: ITISFG</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Agricultural machinery ; Algorithms ; Axles ; Data integration ; Distance measurement ; Dynamic models ; Estimates ; Estimation ; Faces ; Hitch angle estimation ; Kalman filter ; Kalman filters ; Kinematics ; Low speed ; Mathematical model ; Sensors ; Towing ; Tractor trailers ; Tractors ; trailer axle location estimation ; trailer mass estimation ; ultra-sonic sensors</subject><ispartof>IEEE transactions on intelligent transportation systems, 2022-07, Vol.23 (7), p.7535-7546</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-b1f998a73523bc522947526a59d8eafacd88826ac831ebb6464b7a58834dc2983</citedby><cites>FETCH-LOGICAL-c293t-b1f998a73523bc522947526a59d8eafacd88826ac831ebb6464b7a58834dc2983</cites><orcidid>0000-0003-3263-7084 ; 0000-0002-1998-6100 ; 0000-0002-5333-0201</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9406439$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9406439$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Habibnejad Korayem, Amin</creatorcontrib><creatorcontrib>Pazooki, Alireza</creatorcontrib><creatorcontrib>Durali, Laleh</creatorcontrib><creatorcontrib>Khajepour, Amir</creatorcontrib><creatorcontrib>Fidan, Baris</creatorcontrib><creatorcontrib>Ponnuswami, Anushya Viraliur</creatorcontrib><creatorcontrib>Khaligh, Sepehr Pourrezaei</creatorcontrib><title>Hitch Angle Estimation of a Towing Vehicle With Arbitrary Configuration</title><title>IEEE transactions on intelligent transportation systems</title><addtitle>TITS</addtitle><description>In this paper, ultra-sonic sensors along with kinematics and dynamics equations of a towing vehicle are used to develop three approaches for hitch angle estimation. The first approach is based on direct calculation of hitch angle using certain a priori geometric information and distance measurements of four ultra-sonic sensors. An angle estimate is generated for each of the six possible sensor-pair combinations, and these six estimates are passed through a voting algorithm to produce a single estimate. As the second and third approaches, kinematic and dynamic models of the tractor-trailer system are used to develop least-squares and Kalman filtering based recursive hitch angle estimations. A more reliable hitch angle estimation scheme is then proposed as the integration of the algorithms developed following each of the three approaches via a switching data fusion logic. It is shown that the proposed integrated hitch angle estimation scheme can be used for any ball type box trailer with a flat or symmetric V-nose frontal face without any priori information on the trailer parameters. Based on the validity of the assumptions, the proposed scheme can estimate the hitch angle in both low-speed using the kinematic model, and high-speed using the dynamic model of the tractor-trailer system. Experimental results corroborate the algorithms in estimating the hitch angle estimates in various cases conducted in this study.</description><subject>Agricultural machinery</subject><subject>Algorithms</subject><subject>Axles</subject><subject>Data integration</subject><subject>Distance measurement</subject><subject>Dynamic models</subject><subject>Estimates</subject><subject>Estimation</subject><subject>Faces</subject><subject>Hitch angle estimation</subject><subject>Kalman filter</subject><subject>Kalman filters</subject><subject>Kinematics</subject><subject>Low speed</subject><subject>Mathematical model</subject><subject>Sensors</subject><subject>Towing</subject><subject>Tractor trailers</subject><subject>Tractors</subject><subject>trailer axle location estimation</subject><subject>trailer mass estimation</subject><subject>ultra-sonic sensors</subject><issn>1524-9050</issn><issn>1558-0016</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kMtOAjEUhhujiYg-gHHTxPVgr9N2SQgCCYkLR102ndKBEpxip8Tw9nSEuDq3_z8n5wPgEaMRxki9VIvqfUQQwSOKBKYKX4EB5lwWCOHyus8JKxTi6Bbcdd02dxnHeABmc5_sBo7b9c7BaZf8t0k-tDA00MAq_Pp2DT_dxts8_vIpK2PtUzTxCCehbfz6EP8M9-CmMbvOPVziEHy8TqvJvFi-zRaT8bKwRNFU1LhRShpBOaG15YQoJjgpDVcr6Uxj7EpKmWsrKXZ1XbKS1cJwKSlb5Q2SDsHzee8-hp-D65LehkNs80lNSikFokqIrMJnlY2h66Jr9D7mz-JRY6R7XrrnpXte-sIre57OHu-c-9crhkpGFT0BHjplfw</recordid><startdate>20220701</startdate><enddate>20220701</enddate><creator>Habibnejad Korayem, Amin</creator><creator>Pazooki, Alireza</creator><creator>Durali, Laleh</creator><creator>Khajepour, Amir</creator><creator>Fidan, Baris</creator><creator>Ponnuswami, Anushya Viraliur</creator><creator>Khaligh, Sepehr Pourrezaei</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>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0003-3263-7084</orcidid><orcidid>https://orcid.org/0000-0002-1998-6100</orcidid><orcidid>https://orcid.org/0000-0002-5333-0201</orcidid></search><sort><creationdate>20220701</creationdate><title>Hitch Angle Estimation of a Towing Vehicle With Arbitrary Configuration</title><author>Habibnejad Korayem, Amin ; Pazooki, Alireza ; Durali, Laleh ; Khajepour, Amir ; Fidan, Baris ; Ponnuswami, Anushya Viraliur ; Khaligh, Sepehr Pourrezaei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-b1f998a73523bc522947526a59d8eafacd88826ac831ebb6464b7a58834dc2983</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Agricultural machinery</topic><topic>Algorithms</topic><topic>Axles</topic><topic>Data integration</topic><topic>Distance measurement</topic><topic>Dynamic models</topic><topic>Estimates</topic><topic>Estimation</topic><topic>Faces</topic><topic>Hitch angle estimation</topic><topic>Kalman filter</topic><topic>Kalman filters</topic><topic>Kinematics</topic><topic>Low speed</topic><topic>Mathematical model</topic><topic>Sensors</topic><topic>Towing</topic><topic>Tractor trailers</topic><topic>Tractors</topic><topic>trailer axle location estimation</topic><topic>trailer mass estimation</topic><topic>ultra-sonic sensors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Habibnejad Korayem, Amin</creatorcontrib><creatorcontrib>Pazooki, Alireza</creatorcontrib><creatorcontrib>Durali, Laleh</creatorcontrib><creatorcontrib>Khajepour, Amir</creatorcontrib><creatorcontrib>Fidan, Baris</creatorcontrib><creatorcontrib>Ponnuswami, Anushya Viraliur</creatorcontrib><creatorcontrib>Khaligh, Sepehr Pourrezaei</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on intelligent transportation systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Habibnejad Korayem, Amin</au><au>Pazooki, Alireza</au><au>Durali, Laleh</au><au>Khajepour, Amir</au><au>Fidan, Baris</au><au>Ponnuswami, Anushya Viraliur</au><au>Khaligh, Sepehr Pourrezaei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Hitch Angle Estimation of a Towing Vehicle With Arbitrary Configuration</atitle><jtitle>IEEE transactions on intelligent transportation systems</jtitle><stitle>TITS</stitle><date>2022-07-01</date><risdate>2022</risdate><volume>23</volume><issue>7</issue><spage>7535</spage><epage>7546</epage><pages>7535-7546</pages><issn>1524-9050</issn><eissn>1558-0016</eissn><coden>ITISFG</coden><abstract>In this paper, ultra-sonic sensors along with kinematics and dynamics equations of a towing vehicle are used to develop three approaches for hitch angle estimation. The first approach is based on direct calculation of hitch angle using certain a priori geometric information and distance measurements of four ultra-sonic sensors. An angle estimate is generated for each of the six possible sensor-pair combinations, and these six estimates are passed through a voting algorithm to produce a single estimate. As the second and third approaches, kinematic and dynamic models of the tractor-trailer system are used to develop least-squares and Kalman filtering based recursive hitch angle estimations. A more reliable hitch angle estimation scheme is then proposed as the integration of the algorithms developed following each of the three approaches via a switching data fusion logic. It is shown that the proposed integrated hitch angle estimation scheme can be used for any ball type box trailer with a flat or symmetric V-nose frontal face without any priori information on the trailer parameters. Based on the validity of the assumptions, the proposed scheme can estimate the hitch angle in both low-speed using the kinematic model, and high-speed using the dynamic model of the tractor-trailer system. Experimental results corroborate the algorithms in estimating the hitch angle estimates in various cases conducted in this study.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TITS.2021.3071391</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-3263-7084</orcidid><orcidid>https://orcid.org/0000-0002-1998-6100</orcidid><orcidid>https://orcid.org/0000-0002-5333-0201</orcidid></addata></record> |
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subjects | Agricultural machinery Algorithms Axles Data integration Distance measurement Dynamic models Estimates Estimation Faces Hitch angle estimation Kalman filter Kalman filters Kinematics Low speed Mathematical model Sensors Towing Tractor trailers Tractors trailer axle location estimation trailer mass estimation ultra-sonic sensors |
title | Hitch Angle Estimation of a Towing Vehicle With Arbitrary Configuration |
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