{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:14:21Z","timestamp":1760238861585,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2020,9,8]],"date-time":"2020-09-08T00:00:00Z","timestamp":1599523200000},"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>Over the past decades, both industry and academy have made enormous advancements in the field of intelligent vehicles, and a considerable number of prototypes are now driving our roads, railways, air and sea autonomously. However, there is still a long way to go before a widespread adoption. Among all the scientific and technical problems to be solved by intelligent vehicles, the ability to perceive, interpret, and fully understand the operational environment, as well as to infer future states and potential hazards, represent the most difficult and complex tasks, being probably the main bottlenecks that the scientific community and industry must solve in the coming years to ensure the safe and efficient operation of the vehicles (and, therefore, their future adoption). The great complexity and the almost infinite variety of possible scenarios in which an intelligent vehicle must operate, raise the problem of perception as an \"endless\" issue that will always be ongoing. As a humble contribution to the advancement of vehicles endowed with intelligence, we organized the Special Issue on Intelligent Vehicles. This work offers a complete analysis of all the mansucripts published, and presents the main conclusions drawn.<\/jats:p>","DOI":"10.3390\/s20185115","type":"journal-article","created":{"date-parts":[[2020,9,8]],"date-time":"2020-09-08T09:03:48Z","timestamp":1599555828000},"page":"5115","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Sensors and Sensing for Intelligent Vehicles"],"prefix":"10.3390","volume":"20","author":[{"given":"David","family":"Fern\u00e1ndez Llorca","sequence":"first","affiliation":[{"name":"Computer Engineering Department, University of Alcal\u00e1, 28805 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8940-6434","authenticated-orcid":false,"given":"Iv\u00e1n","family":"Garc\u00eda Daza","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, University of Alcal\u00e1, 28805 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Noelia","family":"Hern\u00e1ndez Parra","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, University of Alcal\u00e1, 28805 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ignacio","family":"Parra Alonso","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, University of Alcal\u00e1, 28805 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,8]]},"reference":[{"key":"ref_1","unstructured":"Gavrila, D.M. 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