Driving Decisions

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.