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The path to autonomous driving
Journal of AI, Robotics & Workplace Automation,
1
(1),
34-42
(2021)
Abstract
We are in 2021, the year many automakers had promised self-driving cars. The reality is that as we get ready to reclaim our mobility that was limited because of the COVID-19 pandemic, there is still no agreement among industry experts on when we will reach full autonomous driving. The pandemic has created a shift in the market drivers, however, influencing the path for consumer adoption of vehicle autonomy, new business models using Level 4 instead of Level 5 and increased digitisation with data and artificial intelligence (AI) in vehicles. This paper analyses shifts in five key market drivers: technology, consumer adoption, business model shifts, data platforms in vehicles, adoption of electric vehicles and advanced driver assist systems (ADAS) features by carmakers, and proposes three potential paths towards autonomous driving.
Keywords: autonomous cars; self-driving cars; driverless cars; technology and driverless world; full autonomy; autonomous vehicles; advanced driver assist systems (ADAS); connected vehicles; data in the car; AI in the car; data; artificial intelligence (AI)
The full article is available to subscribers to the journal.
Author's Biography
Sudha Jamthe is a globally recognised technology futurist with a 20+ year mix of entrepreneurial, academic and operational experience in the technology industry. She brings focused research on the business of data with a futuristic lens on value creation from data, and ethical human-centred design of artificial intelligence (AI). Sudha is the author of six books and teaches Internet of Things (IoT), AI and autonomous vehicles business courses at Stanford Continuing Studies and at BusinessSchoolofAI.com. Sudha teaches AI ethics courses to three Master’s programmes at Barcelona Technology School. She serves as the chair of the strategic advisory board for Barcelona Technology School and as an ambassador for FundingBox Impact Connected Cars (Europe H2020) Community and NGI. Sudha has an MBA from Boston University and BS in computer science engineering from Madras University.
Ananya Sen has been building enterprise software for 12 years’ in the Bay Area, with an eye for artificial intelligence, audio/video, security and data analytics. Ananya has been passionate about giving back to the community, via speaking at the Grace Hopper Conference 2014, weekly webinars at Business School of AI and blogs. Currently she is a product manager at LexisNexis® ThreatMetrix®, which is an enterprise fraud detection and analytics solution, using global identity intelligence, machine learning and advanced big data analytics. Before this, she was a software engineer at Intuit, in several platform groups for cloud and financial data. Ananya did her MS in Enterprise Software Technologies at San Jose State University, and Product Management studies from Stanford Continuing Studies. She loves to swim, sing and spend time with her son.
