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To mitigate the grave consequence of using incorrect data, we propose\n                    <jats:monospace>CADCA<\/jats:monospace>\n                    , a novel control decision-maker for SAVs, that is designed to operate under sensor\/data errors or falsifications as well as malicious\/erroneous control inputs with the ultimate goal of resolving conflicting control inputs to ensure safety. Our evaluation of\n                    <jats:inline-formula content-type=\"math\/tex\">\n                      <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\( &gt; \\)<\/jats:tex-math>\n                    <\/jats:inline-formula>\n                    15,700 test-cases has shown\n                    <jats:monospace>CADCA<\/jats:monospace>\n                    to achieve a 98% success rate in preventing the execution of incorrect control decisions caused by component failures and\/or malicious attacks in the most common (i.e., rear-end) collisions.\n                  <\/jats:p>","DOI":"10.1145\/3777456","type":"journal-article","created":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T15:39:51Z","timestamp":1763480391000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Design of Safer Control for Semi-Autonomous Vehicles"],"prefix":"10.1145","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1820-1719","authenticated-orcid":false,"given":"Chun-Yu","family":"Chen","sequence":"first","affiliation":[{"name":"CSE\/EECS, University of Michigan, Ann Arbor, Michigan, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0086-8777","authenticated-orcid":false,"given":"Kang G.","family":"Shin","sequence":"additional","affiliation":[{"name":"CSE\/EECS, University of Michigan, Ann Arbor, Michigan, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,1,20]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"National Highway Traffic Safety Administration US Department of Transportation. 2015. 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