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Driving decisionshow autonomous vehicles make sense of the world /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Driving decisionsby Sam Hind.
Reminder of title:	how autonomous vehicles make sense of the world /
Author:	Hind, Sam.
Published:	Singapore :Springer Nature Singapore :2024.
Description:	xv, 269 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Automated vehiclesDecision making.
Online resource:	https://doi.org/10.1007/978-981-97-1749-1
ISBN:	9789819717491$q(electronic bk.)

Driving decisionshow autonomous vehicles make sense of the world /
Hind, Sam.

Driving decisionshow autonomous vehicles make sense of the world /[electronic resource] :by Sam Hind. - Singapore :Springer Nature Singapore :2024. - xv, 269 p. :ill., digital ;24 cm.

1. 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.

This 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.

ISBN: 9789819717491$q(electronic bk.)

Standard No.: 10.1007/978-981-97-1749-1doiSubjects--Topical Terms:

858838
Automated vehicles
--Decision making.

LC Class. No.: TL152.8

Dewey Class. No.: 629.046

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505 0 $a 1. 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 $a This 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.
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