04103nam a22005055i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001500172072001500187072002300202072001400225100014600239245011200385250001800497264008200515300004300597336002600640337002600666338003600692347002400728505044900752520183601201650003603037650002803073650003503101650003603136650004303172650002803215650002603243650003303269650003603302710003403338773002603372776003603398776003603434776003603470856004603506912001403552912001403566999001703580978-981-97-1749-1DE-He21320251030112846.0cr nn 008mamaa240809s2024    si |    s    |||| 0|eng d  a97898197174919978-981-97-1749-17 a10.1007/978-981-97-1749-12doi 4aQ175.4-.55 7aJF2bicssc 7aSOC0000002bisacsh 7aJB2thema1 aHind, Sam.eauthor.0(orcid)0000-0001-8347-36951https://orcid.org/0000-0001-8347-36954aut4http://id.loc.gov/vocabulary/relators/aut98213410aDriving Decisionsh[electronic resource] :bHow Autonomous Vehicles Make Sense of the World /cby Sam Hind.  a1st ed. 2024. 1aSingapore :bSpringer Nature Singapore :bImprint: Palgrave Macmillan,c2024.  aXV, 269 p. 31 illus.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda0 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.  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. . 0aSciencexSocial aspects.969032 0aHuman geography.958506 0aMass media and culture.967749 0aArtificial intelligence.95844114aScience and Technology Studies.96903324aHuman Geography.95850624aMedia Culture.96775124aSociology of Science.98213524aArtificial Intelligence.9584412 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978981971748408iPrinted edition:z978981971750708iPrinted edition:z978981971751440uhttps://doi.org/10.1007/978-981-97-1749-1  aZDB-2-SLS  aZDB-2-SXS  c62355d62355