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Advanced Sensing and Control for Connected and Automated Vehicles

Objektkategorie:
Elektronische Ressource
Person/Institution:
Huang, Chao
Du, Haiping
Zhao, Wanzhong
Zhao, Yifan
Yan, Fuwu
Lv, Chen
Verlag:
MDPI - Multidisciplinary Digital Publishing Institute
Veröffentlichungsort:
Basel
Entstehungszeit:
2022
Umfang, Illustration, Format:
1 Online-Ressource (284 p.)
Sprache:
Nicht zu entscheiden
Bereitstellende Institution:
Forschungsbibliothek Gotha
GND Explorer
Abstract:
Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a hotspot in recent years. Thanks to improved sensing technologies, CAVs are able to interpret sensory information to further detect obstacles, localize their positions, navigate themselves, and interact with other surrounding vehicles in the dynamic environment. Furthermore, leveraging computer vision and other sensing methods, in-cabin humans' body activities, facial emotions, and even mental states can also be recognized. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in the sensing and control of CAVs
Objekttext:
English

Zugriff und Nutzungsmöglichkeiten

Universität Erfurt
Forschungsbibliothek Gotha
Schloss Friedenstein
Schlossplatz 1
99867 Gotha
+49 361 737-5540
bibliothek.gotha(at)uni-erfurt.de
Datensatz angelegt am:
2023-04-12
Zuletzt geändert am:
2023-01-29
In Portal übernommen am:
2023-04-12