Neural networks are making their ways into various commercial products across many industries. As in aerospace, in automotive industry they are not the main technology. Automotive engineers and researchers are certainly familiar with the buzzword, and some have even tried neural networks for their specific applications as models, virtual sensors, or controllers (see, e.g., [1] for a collection of relevant papers). In fact, a quick search reveals scores of recent papers on automotive applications of NN, fuzzy, evolutionary and other technologies of computational intelligence (CI); see, e.g., [2–4]. However, such technologies are mostly at the stage of research and not in the mainstream of product development yet. One of the reasons is “black-box” nature of neural networks. Other, perhaps more compelling reasons are business conservatism and existing/legacy applications (trying something new costs money and might be too risky) [5, 6].
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Prokhorov, D. (2008). Neural Networks in Automotive Applications. In: Prokhorov, D. (eds) Computational Intelligence in Automotive Applications. Studies in Computational Intelligence, vol 132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79257-4_7
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