全球智库信息集成服务系统

Results Suggest That More Lives Will Be Saved the Sooner HAVs Are Deployed

• We used the RAND Model of Automated Vehicle Safety to compare road fatalities under (1) a policy that allows HAVs to be deployed for consumer use when their safety performance is just 10 percent better than that of the average human driver (Improve10) and (2) a policy that waits to deploy HAVs only once they have reached significant performance improvements of 75 percent or 90 percent (Improve75 or Improve90).
• We find that, in the short term, more lives are cumulatively saved under a more permissive policy (Improve10) than stricter policies requiring greater safety advancements (Improve75 or Improve90) in nearly all conditions, and those savings can be significant — hundreds of thousands of lives.
• In the long term, more lives are cumulatively saved under an Improve10 policy than either Improve75 or Improve90 policies under all combinations of conditions we explored. In many cases, those savings can be more than half a million lives.
• There is good reason to believe that reaching significant safety improvements may take a long time and may be difficult prior to deployment. Therefore, the number of lives lost while waiting for significant improvements prior to deployment may be large.

How safe should highly automated vehicles (HAVs) be before they are allowed on the roads for consumer use? This question underpins much of the debate around how and when to introduce and use the technology so that the potential risks from HAVs are minimized and the benefits maximized. In this report, we use the RAND Model of Automated Vehicle Safety to compare road fatalities over time under (1) a policy that allows HAVs to be deployed for consumer use when their safety performance is just 10 percent better than that of the average human driver and (2) a policy that waits to deploy HAVs only once their safety performance is 75 or 90 percent better than that of average human drivers — what some might consider nearly perfect. We find that, in the long term, under none of the conditions we explored does waiting for significant safety gains result in fewer fatalities. At best, fatalities are comparable, but, at worst, waiting has high human costs — in some cases, more than half a million lives. Moreover, the conditions that might lead to comparable fatalities — rapid improvement in HAV safety performance that can occur without widespread deployment — seem implausible. This suggests that the opportunity cost, in terms of lives saved, for waiting for better HAV performance may indeed be large. This evidence can help decisionmakers better understand the human cost of different policy choices governing HAV safety and set policies that save more lives.

• Chapter One

  Introduction

• Chapter Two

  Definitions and Prior Work

• Chapter Three

  Methods

• Chapter Four

  Analytical Results

• Chapter Five

  Policy Implications and Conclusions