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024 7 _a10.1007/978-981-97-1749-1
_2doi
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100 1 _aHind, Sam.
_eauthor.
_0(orcid)0000-0001-8347-3695
_1https://orcid.org/0000-0001-8347-3695
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_982134
245 1 0 _aDriving Decisions
_h[electronic resource] :
_bHow Autonomous Vehicles Make Sense of the World /
_cby Sam Hind.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Palgrave Macmillan,
_c2024.
300 _aXV, 269 p. 31 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _a1. Introduction: The Making of Decisions and Technological Decisionism -- 2. Mapping Decisions: The Promise of Mapless-ness -- 3. Training Decisions: Ground-Truthing the Interesting -- 4. Sensing Decisions: Perceiving, Classifying, Finessing -- 5. Demonstrating Decisions: Waymo’s World -- 6. Securing Decisions: Sovereignty and Semiconductors -- 7. Relaxing Decisions: Making Driving Chill -- 8. Resisting Decisions: Coneheads in California.
520 _aThis book examines the phenomenon of autonomous driving, and the ongoing, complex, costly, and contentious quest to automate driving. It is organized around the concept of algorithmic decision-making, with a particular focus on the ‘advance decisions’ necessary to automate driving, and driving decisions as rudimentary as turning a corner, merging onto a motorway, or stopping at traffic lights. The author investigates how mapping, sensing, and machine learning capabilities are gifted to autonomous vehicles through the technical work performed by an array of actors in multiple locations: from users of advanced driver assistance devices enthusiastically serving as volunteer data collectors, to graduate students developing computational solutions in university research initiatives, and from software developers running computer simulations at big tech firms to their counterparts at autonomous vehicle start-ups overseeing active robotaxi services. This book intends to complicate, and question, typical understandings of autonomous driving by going ‘under the hood’, challenging the determinism, or ‘technological decisionism’, that advocates depend on to offer their vision of an inevitable, fully automated, future. It will appeal to scholars and students in the fields of Science and Technology Studies, media studies, digital sociology, human geography, mobilities and transport studies, and digital methodologies. Sam Hind is a Lecturer in Digital Media and Culture at the University of Manchester, UK. He researches digital navigation, sensing, and automobility through the lens of algorithmic decision-making. He has studied technological shifts in driving and automotive navigation for over 10 years, with a particular interest in how big tech companies have sought to disrupt the automotive industry. .
650 0 _aScience
_xSocial aspects.
_969032
650 0 _aHuman geography.
_958506
650 0 _aMass media and culture.
_967749
650 0 _aArtificial intelligence.
_958441
650 1 4 _aScience and Technology Studies.
_969033
650 2 4 _aHuman Geography.
_958506
650 2 4 _aMedia Culture.
_967751
650 2 4 _aSociology of Science.
_982135
650 2 4 _aArtificial Intelligence.
_958441
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819717484
776 0 8 _iPrinted edition:
_z9789819717507
776 0 8 _iPrinted edition:
_z9789819717514
856 4 0 _uhttps://doi.org/10.1007/978-981-97-1749-1
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912 _aZDB-2-SXS
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