Test Scenario Design for Intelligent Driving System Ensuring Coverage and Effectiveness
Intelligent vehicle greatly benefits traffic safety, efficiency and driving comfortable. With the development of intelligent driving technology and its application, it is becoming increasingly important to do effective and comprehensive tests before putting on the market. Comprehensively considering...
Gespeichert in:
| Veröffentlicht in: | International journal of automotive technology 2018-08, Vol.19 (4), p.751-758 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 758 |
|---|---|
| container_issue | 4 |
| container_start_page | 751 |
| container_title | International journal of automotive technology |
| container_volume | 19 |
| creator | Xia, Qin Duan, Jianli Gao, Feng Hu, Qiuxia He, Yingdong |
| description | Intelligent vehicle greatly benefits traffic safety, efficiency and driving comfortable. With the development of intelligent driving technology and its application, it is becoming increasingly important to do effective and comprehensive tests before putting on the market. Comprehensively considering the cost of test, an automatic generation method of test scenarios is proposed to ensure both coverage and effectiveness. Based on the analyzed key infuence factors of an intelligent driving system, the analytic hierarchy process (AHP) is used to determine their importance and accordingly an complex index is defined, based on which an improved test case generation algorithm based on the pairwise independent combinatorial testing tool (PICT) is proposed to ensuring both combinational coverage and complexity of test cases. Finally, the test scenario is generated by clustering these discrete test cases considering similarity and complexity. The high complex test cases are preferred to be combined together and conducted preferentially to increase the test efficiency. The effectiveness of this method is validated by applying it on a lane departure warning system (LDW). |
| doi_str_mv | 10.1007/s12239-018-0072-6 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_sprin</sourceid><recordid>TN_cdi_proquest_journals_2476053785</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2476053785</sourcerecordid><originalsourceid>FETCH-LOGICAL-p156t-b01fe5a2f37b6a24549796566fa0036e7b14bfe116d907deb428c16217e7a7b3</originalsourceid><addsrcrecordid>eNpFkE1LAzEQhoMoWKs_wFvAczSTbJLNUdpaCwUPLXgM2XaybKnZmmwX_PfuUsHTzAsP8_EQ8gj8GTg3LxmEkJZxKNkQBdNXZALWaCZLKa6HXgjLLMjyltzlfOBcaZB8Qj63mDu62WH0qWnpHHNTRxraRFexw-OxqTF2dJ6avok13fzkDr_oIuZzGvOs7TH5GqmPe7oIAXdd02PEnO_JTfDHjA9_dUq2b4vt7J2tP5ar2euanUDpjlUcAiovgjSV9qJQhTVWK62D51xqNBUUVUAAvbfc7LEqRLkDLcCg8aaSU_J0GXtK7fd5eMUd2nOKw0YnCqO5kqZUAyUuVD6NZ2P6p4C70Z-7-HODPzf6c1r-AiDCYxc</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2476053785</pqid></control><display><type>article</type><title>Test Scenario Design for Intelligent Driving System Ensuring Coverage and Effectiveness</title><source>Springer Nature - Complete Springer Journals</source><creator>Xia, Qin ; Duan, Jianli ; Gao, Feng ; Hu, Qiuxia ; He, Yingdong</creator><creatorcontrib>Xia, Qin ; Duan, Jianli ; Gao, Feng ; Hu, Qiuxia ; He, Yingdong</creatorcontrib><description>Intelligent vehicle greatly benefits traffic safety, efficiency and driving comfortable. With the development of intelligent driving technology and its application, it is becoming increasingly important to do effective and comprehensive tests before putting on the market. Comprehensively considering the cost of test, an automatic generation method of test scenarios is proposed to ensure both coverage and effectiveness. Based on the analyzed key infuence factors of an intelligent driving system, the analytic hierarchy process (AHP) is used to determine their importance and accordingly an complex index is defined, based on which an improved test case generation algorithm based on the pairwise independent combinatorial testing tool (PICT) is proposed to ensuring both combinational coverage and complexity of test cases. Finally, the test scenario is generated by clustering these discrete test cases considering similarity and complexity. The high complex test cases are preferred to be combined together and conducted preferentially to increase the test efficiency. The effectiveness of this method is validated by applying it on a lane departure warning system (LDW).</description><identifier>ISSN: 1229-9138</identifier><identifier>EISSN: 1976-3832</identifier><identifier>DOI: 10.1007/s12239-018-0072-6</identifier><language>eng</language><publisher>Seoul: The Korean Society of Automotive Engineers</publisher><subject>Algorithms ; Analytic hierarchy process ; Automotive Engineering ; Clustering ; Combinatorial analysis ; Complexity ; Engineering ; Intelligent vehicles ; Lane keeping ; Traffic safety ; Warning systems</subject><ispartof>International journal of automotive technology, 2018-08, Vol.19 (4), p.751-758</ispartof><rights>The Korean Society of Automotive Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018</rights><rights>The Korean Society of Automotive Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-p156t-b01fe5a2f37b6a24549796566fa0036e7b14bfe116d907deb428c16217e7a7b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12239-018-0072-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12239-018-0072-6$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Xia, Qin</creatorcontrib><creatorcontrib>Duan, Jianli</creatorcontrib><creatorcontrib>Gao, Feng</creatorcontrib><creatorcontrib>Hu, Qiuxia</creatorcontrib><creatorcontrib>He, Yingdong</creatorcontrib><title>Test Scenario Design for Intelligent Driving System Ensuring Coverage and Effectiveness</title><title>International journal of automotive technology</title><addtitle>Int.J Automot. Technol</addtitle><description>Intelligent vehicle greatly benefits traffic safety, efficiency and driving comfortable. With the development of intelligent driving technology and its application, it is becoming increasingly important to do effective and comprehensive tests before putting on the market. Comprehensively considering the cost of test, an automatic generation method of test scenarios is proposed to ensure both coverage and effectiveness. Based on the analyzed key infuence factors of an intelligent driving system, the analytic hierarchy process (AHP) is used to determine their importance and accordingly an complex index is defined, based on which an improved test case generation algorithm based on the pairwise independent combinatorial testing tool (PICT) is proposed to ensuring both combinational coverage and complexity of test cases. Finally, the test scenario is generated by clustering these discrete test cases considering similarity and complexity. The high complex test cases are preferred to be combined together and conducted preferentially to increase the test efficiency. The effectiveness of this method is validated by applying it on a lane departure warning system (LDW).</description><subject>Algorithms</subject><subject>Analytic hierarchy process</subject><subject>Automotive Engineering</subject><subject>Clustering</subject><subject>Combinatorial analysis</subject><subject>Complexity</subject><subject>Engineering</subject><subject>Intelligent vehicles</subject><subject>Lane keeping</subject><subject>Traffic safety</subject><subject>Warning systems</subject><issn>1229-9138</issn><issn>1976-3832</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNpFkE1LAzEQhoMoWKs_wFvAczSTbJLNUdpaCwUPLXgM2XaybKnZmmwX_PfuUsHTzAsP8_EQ8gj8GTg3LxmEkJZxKNkQBdNXZALWaCZLKa6HXgjLLMjyltzlfOBcaZB8Qj63mDu62WH0qWnpHHNTRxraRFexw-OxqTF2dJ6avok13fzkDr_oIuZzGvOs7TH5GqmPe7oIAXdd02PEnO_JTfDHjA9_dUq2b4vt7J2tP5ar2euanUDpjlUcAiovgjSV9qJQhTVWK62D51xqNBUUVUAAvbfc7LEqRLkDLcCg8aaSU_J0GXtK7fd5eMUd2nOKw0YnCqO5kqZUAyUuVD6NZ2P6p4C70Z-7-HODPzf6c1r-AiDCYxc</recordid><startdate>20180801</startdate><enddate>20180801</enddate><creator>Xia, Qin</creator><creator>Duan, Jianli</creator><creator>Gao, Feng</creator><creator>Hu, Qiuxia</creator><creator>He, Yingdong</creator><general>The Korean Society of Automotive Engineers</general><general>Springer Nature B.V</general><scope>3V.</scope><scope>7TB</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K60</scope><scope>K6~</scope><scope>KB.</scope><scope>L.-</scope><scope>M0C</scope><scope>M2P</scope><scope>PDBOC</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope></search><sort><creationdate>20180801</creationdate><title>Test Scenario Design for Intelligent Driving System Ensuring Coverage and Effectiveness</title><author>Xia, Qin ; Duan, Jianli ; Gao, Feng ; Hu, Qiuxia ; He, Yingdong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p156t-b01fe5a2f37b6a24549796566fa0036e7b14bfe116d907deb428c16217e7a7b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Algorithms</topic><topic>Analytic hierarchy process</topic><topic>Automotive Engineering</topic><topic>Clustering</topic><topic>Combinatorial analysis</topic><topic>Complexity</topic><topic>Engineering</topic><topic>Intelligent vehicles</topic><topic>Lane keeping</topic><topic>Traffic safety</topic><topic>Warning systems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xia, Qin</creatorcontrib><creatorcontrib>Duan, Jianli</creatorcontrib><creatorcontrib>Gao, Feng</creatorcontrib><creatorcontrib>Hu, Qiuxia</creatorcontrib><creatorcontrib>He, Yingdong</creatorcontrib><collection>ProQuest Central (Corporate)</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>ABI/INFORM Complete</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Materials Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>ProQuest Science Journals</collection><collection>Materials Science Collection</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><jtitle>International journal of automotive technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xia, Qin</au><au>Duan, Jianli</au><au>Gao, Feng</au><au>Hu, Qiuxia</au><au>He, Yingdong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Test Scenario Design for Intelligent Driving System Ensuring Coverage and Effectiveness</atitle><jtitle>International journal of automotive technology</jtitle><stitle>Int.J Automot. Technol</stitle><date>2018-08-01</date><risdate>2018</risdate><volume>19</volume><issue>4</issue><spage>751</spage><epage>758</epage><pages>751-758</pages><issn>1229-9138</issn><eissn>1976-3832</eissn><abstract>Intelligent vehicle greatly benefits traffic safety, efficiency and driving comfortable. With the development of intelligent driving technology and its application, it is becoming increasingly important to do effective and comprehensive tests before putting on the market. Comprehensively considering the cost of test, an automatic generation method of test scenarios is proposed to ensure both coverage and effectiveness. Based on the analyzed key infuence factors of an intelligent driving system, the analytic hierarchy process (AHP) is used to determine their importance and accordingly an complex index is defined, based on which an improved test case generation algorithm based on the pairwise independent combinatorial testing tool (PICT) is proposed to ensuring both combinational coverage and complexity of test cases. Finally, the test scenario is generated by clustering these discrete test cases considering similarity and complexity. The high complex test cases are preferred to be combined together and conducted preferentially to increase the test efficiency. The effectiveness of this method is validated by applying it on a lane departure warning system (LDW).</abstract><cop>Seoul</cop><pub>The Korean Society of Automotive Engineers</pub><doi>10.1007/s12239-018-0072-6</doi><tpages>8</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1229-9138 |
| ispartof | International journal of automotive technology, 2018-08, Vol.19 (4), p.751-758 |
| issn | 1229-9138 1976-3832 |
| language | eng |
| recordid | cdi_proquest_journals_2476053785 |
| source | Springer Nature - Complete Springer Journals |
| subjects | Algorithms Analytic hierarchy process Automotive Engineering Clustering Combinatorial analysis Complexity Engineering Intelligent vehicles Lane keeping Traffic safety Warning systems |
| title | Test Scenario Design for Intelligent Driving System Ensuring Coverage and Effectiveness |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-01T16%3A57%3A51IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_sprin&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Test%20Scenario%20Design%20for%20Intelligent%20Driving%20System%20Ensuring%20Coverage%20and%20Effectiveness&rft.jtitle=International%20journal%20of%20automotive%20technology&rft.au=Xia,%20Qin&rft.date=2018-08-01&rft.volume=19&rft.issue=4&rft.spage=751&rft.epage=758&rft.pages=751-758&rft.issn=1229-9138&rft.eissn=1976-3832&rft_id=info:doi/10.1007/s12239-018-0072-6&rft_dat=%3Cproquest_sprin%3E2476053785%3C/proquest_sprin%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2476053785&rft_id=info:pmid/&rfr_iscdi=true |