Cloud-Based Data Analytics for Autonomous Vehicle Performance Using Neural Networks

Cloud-Based Data Analytics for Autonomous Vehicle Performance Using Neural Networks

Delshi Howsalya Devi, P. Santhosh Kumar, M. Aruna, S. Sharmila
Copyright: © 2024 |Pages: 23
DOI: 10.4018/979-8-3693-3597-0.ch005
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Abstract

By utilizing powerful analytical tools and remote computing capabilities, cloud-based data analytics significantly improve the operational efficiency of autonomous cars. Under this model, sensor readings, position data, and system diagnostics among the massive volumes of data produced by autonomous vehicles are sent to a cloud network for immediate analysis. This makes it possible to extract insightful information and trends that improve efficiency, safety, and performance of vehicles. Cloud-based methodology provides scalability, which enables smooth management of substantial datasets, and fosters cooperative endeavours in optimizing algorithms and models for self-governing systems. Analysis of information, machine learning algorithms, and communication are important components of this architecture that work together to enable the ongoing development and enhancement of autonomous vehicle capabilities. In the end, this cutting-edge method enables self-driving cars to negotiate intricate situations with improved decision-making skills, resulting in safer and more dependable driving.
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Literature Review

In the transportation sector, cloud-based autonomous cars have come to light as a game-changer that will transform the way people and commodities move and drive mobility in the future (M. G. Haricharan et al., 2023). In order to improve their capabilities and solve a number of issues, this research investigates the integration of cloud computing in autonomous cars. We investigate the essential elements of cloud-based autonomous cars, such as data processing, real-time communication, and decision-making algorithms, through an extensive analysis of the literature (Muraidhara, P. et al., 2017). The study emphasizes the advantages of cloud infrastructure in providing autonomous cars with improved perception and decision-making capabilities (Serrano, N et al., 2015). These advantages include high-performance processing, large storage, and real-time data analysis (Muraidhara, P. et al., 2019). We also go over the potential and problems that come with cloud-based autonomous cars, such as network latency, data security, privacy, and regulatory issues (Elmurzaevich, M. A. et al., 2022).

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