Special Issue Applications Of Computer Vision To Intelligent Vehicles

Special Issue: Applications of Computer Vision to Intelligent Vehicles

Special Issue of the Manufacturing Engineering Society 2019 (SIMES-2019)

This book derives from the Special Issue of the Manufacturing Engineering Society 2019 (SIMES-2019) that has been launched as a joint issue of the journals Materials and Applied Sciences. The 29 contributions published in this Special Issue of Materials present cutting-edge advances in the field of manufacturing engineering focusing on additive manufacturing and 3D printing; advances and innovations in manufacturing processes; sustainable and green manufacturing; manufacturing of new materials; metrology and quality in manufacturing; industry 4.0; design, modeling, and simulation in manufacturing engineering; and manufacturing engineering and society. Among them, the topic "Additive Manufacturing and 3D Printing" has attracted a large number of contributions in this journal due to its widespread popularity and potential.

Computational Intelligence in Automotive Applications

What is computational intelligence (CI)? Traditionally, CI is understood as a collection of methods from the ?elds of neural networks (NN), fuzzy logic and evolutionary computation. Various de?nitions and opinions exist, but what belongs to CI is still being debated; see, e.g., [1–3]. More recently there has been a proposal to de?ne the CI not in terms of the tools but in terms of challenging problems to be solved [4]. With this edited volume I have made an attempt to give a representative sample of contemporary CI activities in automotive applications to illustrate the state of the art. While CI researchand achievements in some specialized ?elds described (see, e.g., [5, 6]), this is the ?rst volume of its kind dedicated to automotive technology. As if re?ecting the general lack of consensus on what constitutes the ?eld of CI, this volume 1 illustrates automotive applications of not only neural and fuzzy computations which are considered to be the “standard” CI topics, but also others, such as decision trees, graphicalmodels, Support Vector Machines (SVM), multi-agent systems, etc. This book is neither an introductory text, nor a comprehensive overview of all CI research in this area. Hopefully, as a broad and representative sample of CI activities in automotive applications, it will be worth reading for both professionals and students. When the details appear insu?cient, the reader is encouraged to consult other relevant sources provided by the chapter authors.