Autonomous vehicles decision-making enhancement using self-determination theory and mixed-precision neural networks

The safe human-level decision-making for expressing the autonomous vehicles and the estimation of the eco vehicles has been proposed for the motion control for the driving behavior. For efficient decision-making, the sensor-based tracking of the autonomous machine for blockchain is to be done. The s...

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Vydáno v:	Multimedia tools and applications Ročník 84; číslo 29; s. 35263 - 35286
Hlavní autoři:	Ali, Mohammed Hasan, Jaber, Mustafa Musa, Alfred Daniel, J, Vignesh, C. Chandru, Meenakshisundaram, Iyapparaja, Kumar, B. Santhosh, Punitha, P.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.09.2025 Springer Nature B.V
Témata:	1231: IoT-driven Computer Vision Technology for Smart Transportation Applications Artificial intelligence Autonomous vehicles Blockchain Computer Communication Networks Computer Science Data Structures and Information Theory Data transmission Decision making Electric vehicles Motion control Multimedia Information Systems Neural networks Privacy Special Purpose and Application-Based Systems Vehicles Neural Networks Autonomous Vehicles Decision-Making Mixed-Precision Neural Networks Self-Determination Theory
ISSN:	1573-7721, 1380-7501, 1573-7721
On-line přístup:	Získat plný text
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