Autonomous Driving: Technical, Legal and Social Aspects
By Markus Maurer, J. Christian Gerdes, Barbara Lenz, Hermann Winner. 2016
390 citations recorded by the source corpus.
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? Experts from Germany and the United States define key societal, engineering, and mobility issues related to the automation of vehicles. They discuss the decisions programmers of automated vehicles must make to enable vehicles to perceive their environment, interact with other road users, and choose actions that may have ethical consequences. The authors further identify expectations and concerns that will form the basis for individual and societal acceptance of autonomous driving. While the safety benefits of such vehicles are tremendous, the authors demonstrate that these benefits will only be achieved if vehicles have an appropriate safety concept at the heart of their design. Realizing the potential of automated vehicles to reorganize traffic and transform mobility of people and goods requires similar care in the design of vehicles and networks. By covering all ofthese topics, the book aims to provide a current, comprehensive, and scientifically sound treatment of the emerging field of autonomous driving".
Subfields: Automotive Engineering
View Paper: https://www.semanticscholar.org/paper/5ba0e8dd6420c5f620ab7fc7f33f6d956abdbafe
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In Automotive Engineering
Citations in the corpus
- Planning and Decision-Making for Autonomous Vehicles (2018, background): “Achieving the vision of fully capable automated vehicles will require overcoming many technical, legal, and social challenges (7).”
- Accountability of AI Under the Law: The Role of Explanation (2017, neutral): “We expect that they will be soon be applied in safety-critical applications such as clinical decision support [Garg et al., 2005] and autonomous driving [Maurer et al., 2016].”
- LMSeg: Language-guided Multi-dataset Segmentation (2023, background): “Image Segmentation has been a longstanding challenge in computer vision and plays a pivotal role in a wide variety of applications ranging from autonomous driving (Levinson et al., 2011; Maurer et al., 2016) to remote sensing image analysis (Ghassemian, 2016).”
- Automation fears: Drivers and solutions (2020, background): “Automation technologies are used as autonomous vehicles for transporting goods and people (Maurer et al., 2016), in warehousing and supply chain management (Wurman, D’Andrea & Mountz, 2008), in communicating and maintaining relationships with customers through chatbots (Buhalis & Yen, 2020; Hill, Fo”