الصفحة 1
الصفحة 1
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Autonomous driving : Technical, legal and social aspects

This book takes a look at fully automated, autonomous vehicles and discusses many open questions: How can autonomous vehicles be integrated into the current transportation system with diverse users and human drivers? Where do automated vehicles fall under current legal frameworks? What risks are associated with automation and how will society respond to these risks? How will the marketplace react to automated vehicles and what changes may be necessary for companies?

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Autonomes fahren : Technische, rechtliche und gesellschaftliche aspekte = Autonomous driving : Technical, legal and social aspects

This book provides answers to a wide range of these and other questions. Experts from Germany and the USA describe central topics related to the automation of vehicles on public roads from an engineering and social science perspective. They show which "decisions" are required of an autonomous vehicle or which "ethics" must be programmed. The authors discuss expectations and concerns that characterize the individual and societal acceptance of autonomous driving. An increased safety potential through autonomous vehicles is compared to the challenges and solution approaches that play a role in securing the safety concept. In addition, they explain what possibilities for change and opportunities arise for our mobility and the reorganization of traffic, not least for freight traffic. The book thus offers an up-to-date, comprehensive and scientifically sound examination of the topic of "autonomous driving".

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Advanced driver assistance system (ADAS)

The purpose of Advanced Driver Assistance Systems (ADAS) is to reduce or eliminate driver errors, and to enhance efficiency in traffic and transportation. Our project is a means and a great contribution to safe driving, and the user does not need to install sensors or hard tools to the vehicle, and through it, the cost can be reduced and maintenance cost can be eliminated. The images are processed and segmented to find different features in the image. Segmented images are used for identification and classification based on various machine learning algorithms and neural networks. The main focus of ADAS technologies is to contribute to factors such as safety management and automated, stress-free driving for the driver

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