Abstract

Automotive Industry is having a rapid progress towards highest level of autonomy. As the industry moves up the ladder of automation, safety features are coming more and more into the focus. Different safety measurements have to be taken into consideration based on different driving situations. One of the major concerns of the highest level of autonomy is to obtain the ability of understanding both internal and external situations. In order to automate this process, first, understanding and automating the situation identification is necessary. Systems will also have to have embedded intelligence of awareness in order to reach to these situations. Situation Awareness is a term that consists of extracting information from the environment, providing an understanding towards the extracted features and taking actions in order to make awareness. This journal focuses on the different levels of situation awareness, provides concepts in order to automate the process so that it can play a vital role towards highly autonomous vehciles.

Highlights

  • Our journal uses electronic publication, which provides a flexible way to submit and review contributions of authors from all of countries

  • Each issue starts with an initial editorial and an official call for papers

  • The submitted articles will be reviewed and, if accepted, published as soon as the final version is received by the committee

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Summary

Julkar Nine

This editorial introduces the third issue of 2020 for Embedded Selforganising Systems (ESS) journal. Our journal uses electronic publication, which provides a flexible way to submit and review contributions of authors from all of countries. The advantages of such an e-journal are multifarious. The submitted articles will be reviewed and, if accepted, published as soon as the final version is received by the committee. Based on this process, each sliding issue can be filled successively until the maximum number of article is reached. We intend to create a promising platform for creative and constructive discussions

Towards Robust Situation Awareness in Autonomous Vehicles
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