Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability?

Kalra, Nidhi; Paddock, Susan M.

doi:10.1016/j.tra.2016.09.010

“…Recent studies (126) have indicated that the minimal requirement to demonstrate safety for an autonomous car is hundreds of millions of miles, taking possibly tens of years to complete. While simulation and case-based testing are routinely employed to check the performance of autonomy methods, they do not provide sufficient guarantees.…”

Section: Verification and Synthesismentioning

confidence: 99%

Planning and Decision-Making for Autonomous Vehicles

Schwarting

¹

,

Alonso–Mora

²

,

Rus

³

2018

Annu. Rev. Control Robot. Auton. Syst.

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In this review, we provide an overview of emerging trends and challenges in the field of intelligent and autonomous, or self-driving, vehicles. Recent advances in the field of perception, planning, and decision-making for autonomous vehicles have led to great improvements in functional capabilities, with several prototypes already driving on our roads and streets. Yet challenges remain regarding guaranteed performance and safety under all driving circumstances. For instance, planning methods that provide safe and systemcompliant performance in complex, cluttered environments while modeling the uncertain interaction with other traffic participants are required. Furthermore, new paradigms, such as interactive planning and end-to-end learning, open up questions regarding safety and reliability that need to be addressed. In this survey, we emphasize recent approaches for integrated perception and planning and for behavior-aware planning, many of which rely on machine learning. This raises the question of verification and safety, which we also touch upon. Finally, we discuss the state of the art and remaining challenges for managing fleets of autonomous vehicles. 8.1

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“…4 At this time, both questions remain unanswered. RAND research recently showed that the only proven method of testing safety-driving HAVs in real traffic conditions and observing their performance-requires too many miles of driving to be practical prior to widespread consumer use (Kalra and Paddock, 2016). Fortunately, there is much effort being put into developing and validating alternative methods, including accelerated testing on roads and in simulation (Zhao and Peng, 2017;Google Auto LLC, 2016) and testing for behavioral competency at closed courses and proving grounds (Nowakowski et al, 2017;U.S.…”

Section: Introductionmentioning

confidence: 99%

The Enemy of Good: Estimating the Cost of Waiting for Nearly Perfect Automated Vehicles

Kalra¹,

Groves²

2017

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This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited. Permission is given to duplicate this document for personal use only, as long as it is unaltered and complete. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial use. For information on reprint and linking permissions, please visit www.rand.org/pubs/permissions.The RAND Corporation is a research organization that develops solutions to public policy challenges to help make communities throughout the world safer and more secure, healthier and more prosperous. RAND is nonprofit, nonpartisan, and committed to the public interest.RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.Support RAND Make a tax-deductible charitable contribution at www.rand.org/giving/contribute www.rand.org For more information on this publication, visit www.rand.org/t/RR2150Library of Congress Cataloging-in-Publication Data is available for this publication.ISBN: 978-0-8330-9937-2 Published by the RAND Corporation, Santa Monica, Calif. © Copyright 2017 RAND CorporationR® is a registered trademark. Cover image: AP Photo/Gene J. Puskar iii PrefaceThe RAND Corporation has a long history of research on intelligent systems. Since the 1950s, with work on chess-playing computers and the Logic Theory Machine, RAND has produced objective, evidence-based research to help inform how society can harness the benefits and manage the risks of intelligent, transformative technologies. RAND's work on autonomous and automated vehicles builds on this firm foundation. RAND Science, Technology, and PolicyThis research was conducted in the RAND Science, Technology, and Policy program, which focuses primarily on the role of scientific development and technological innovation in human behavior, global and regional decisionmaking as it relates to science and technology, and the concurrent effects that science and technology have on policy analysis and policy choices.This program is part of RAND Justice, Infrastructure, and Environment, a division of the RAND Corporation dedicated to improving policy-and decisionmaking in a wide range of policy domains, including civil and criminal justice, infrastructure development and financing, environmental policy, transportation planning and techiv The Enemy of Good: Estimating the Cost of Waiting for Nearly Perfect Automated Vehicles nology, immigration and border protection, public and occupational safety, energy policy, science and innovation policy, space, and telecommunications.During the development of this report and at the time of publication, co-author Nidhi Kalra's spouse served as co-founder and president of Nuro, a machine-learning and robotics start-up company engaged in autonomous vehicle development. He previously served as a principal engineer for Google's driverless car proje...

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“…The RAND report, Driving to Safety: How Many Miles of Driving Would It Take to Demonstrate Autonomous Vehicle Reliability? (Kalra and Paddock, 2016), showed that society cannot use test driving as a means of proving that AVs are safe because such proof requires hundreds of millions-if not billions-of miles of driving. There is a push to develop modeling and simulation methods, test courses, and other means, but these are not yet developed and validated.…”

Section: Lunch Presentation: the Conundrum Of Autonomous Vehicle Safetymentioning

confidence: 99%

“…The more precisely we want to know how safe a disruptive, hard-to-predict technology is, the more risk we need to accept in deploying it to find out. RAND's Driving to Safety report examines "how many miles of driving do you need to prove AV safety" (Kalra and Paddock, 2016). It concludes that there is a tradeoff: The smaller the difference, the more miles needed; the rarer the event (e.g., fatalities), the more miles needed.…”

Section: Lunch Presentation: the Conundrum Of Autonomous Vehicle Safetymentioning

confidence: 99%

Rethinking Insurance and Liability in the Transformative Age of Autonomous Vehicles

Anderson¹,

Kalra²,

Stanley³

et al. 2018

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This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited. Permission is given to duplicate this document for personal use only, as long as it is unaltered and complete. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial use. For information on reprint and linking permissions, please visit www.rand.org/pubs/permissions.The RAND Corporation is a research organization that develops solutions to public policy challenges to help make communities throughout the world safer and more secure, healthier and more prosperous. RAND is nonprofit, nonpartisan, and committed to the public interest.RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.Support RAND Make a tax-deductible charitable contribution at www.rand.org/giving/contribute www.rand.org For more information on this publication, visit www.rand.org/t/CF383Published by the RAND Corporation, Santa Monica, Calif.

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Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability?

Cited by 871 publications

References 6 publications

Planning and Decision-Making for Autonomous Vehicles

Planning and Decision-Making for Autonomous Vehicles

The Enemy of Good: Estimating the Cost of Waiting for Nearly Perfect Automated Vehicles

Rethinking Insurance and Liability in the Transformative Age of Autonomous Vehicles

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