Remote Sensing Data Fusion Techniques, Autonomous Vehicle Driving Perception Algorithms, and Mobility Simulation Tools in Smart Transportation Systems

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F22%3A00002464" target="_blank" >RIV/75081431:_____/22:00002464 - isvavai.cz</a>
Result on the web
<a href="https://addletonacademicpublishers.com/contents-crlsj/2511-volume-14-1-2022/4278-remote-sensing-data-fusion-techniques-autonomous-vehicle-driving-perception-algorithms-and-mobility-simulation-tools-in-smart-transportation-systems" target="_blank" >https://addletonacademicpublishers.com/contents-crlsj/2511-volume-14-1-2022/4278-remote-sensing-data-fusion-techniques-autonomous-vehicle-driving-perception-algorithms-and-mobility-simulation-tools-in-smart-transportation-systems</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Remote Sensing Data Fusion Techniques, Autonomous Vehicle Driving Perception Algorithms, and Mobility Simulation Tools in Smart Transportation Systems
Original language description
The authors aim at a systematic review of remote sensing data fusion techniques, autonomous driving perception algorithms and mobility simulation tools for intelligent transportation systems.
Czech name
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Czech description
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Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50200 - Economics and Business

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Result description