{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T10:21:06Z","timestamp":1783938066564,"version":"3.55.0"},"reference-count":175,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2015,9,11]],"date-time":"2015-09-11T00:00:00Z","timestamp":1441929600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined.<\/jats:p>","DOI":"10.3390\/s150923020","type":"journal-article","created":{"date-parts":[[2015,9,15]],"date-time":"2015-09-15T03:46:33Z","timestamp":1442288793000},"page":"23020-23049","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":89,"title":["Optimization and Control of Cyber-Physical Vehicle Systems"],"prefix":"10.3390","volume":"15","author":[{"given":"Justin","family":"Bradley","sequence":"first","affiliation":[{"name":"Computer Science and Engineering Department, University of Nebraska - Lincoln, 256 Avery Hall, Lincoln, NE 68588, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ella","family":"Atkins","sequence":"additional","affiliation":[{"name":"Aerospace Engineering Department, University of Michigan, 1320 Beal Ave, Ann Arbor, MI 48109, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2015,9,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1287","DOI":"10.1109\/JPROC.2012.2189792","article-title":"Cyber\u2013Physical Systems: A Perspective at the Centennial","volume":"100","author":"Kim","year":"2012","journal-title":"IEEE Proc."},{"key":"ref_2","unstructured":"Berger, C., and Rumpe, B. 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