Automated vehicles—also referred to as self-driving cars, autonomous vehicles, and driverless cars—offer great potential to improve traffic safety and overall quality of life, given that human error is a factor in more than 90 percent of automobile crashes. Traditional automakers and technology firms have already spent billions of dollars on their prototype automated driving systems, but much more work is needed before consumers can begin to reap the benefits of these new technologies.
Recently, some activist groups have urged policymakers to impose new regulations, such as a “vision test” for automated vehicles (AVs), at this early stage of research and development. While such proposals may appear reasonable, they would actually threaten ongoing AV development and the large potential safety and mobility benefits of automated vehicles.
Since its creation five decades ago, the National Highway Traffic Safety Administration (NHTSA) has largely relied on consensus technical standards to inform its auto safety and performance regulations. The National Technology Transfer and Advancement Act of 1995 and subsequent Office of Management and Budget (OMB) Circular A-119 implementation guidance further established that it is the general federal policy for regulatory agencies to incorporate voluntary consensus standards from private standards-setting bodies in lieu of writing government-unique standards. For automated driving systems, those needed private technical standards and standardized test procedures are by and large still under development. Only once these voluntary consensus standards are published may they be ripe for regulatory incorporation by NHTSA.
A recent RAND Corporation report underscores the challenges that lie ahead for technical standardization and eventual regulation of AVs. These challenges will take technical experts years to resolve, and the RAND report’s authors recommend that the federal government undertake research in two areas: human driver data and safety assessment options. The former is to allow more comparisons between technology capabilities and real-world behavior, and the latter is to expand the toolset available to regulators, which has traditionally centered on lagging measures and regulatory process compliance.
As for competently regulating AVs safety similar to how NHTSA issues and enforces Federal Motor Vehicle Safety Standards for conventional vehicles, the report suggests the near-term prospects are slim. In a footnote, the RAND authors note that interviewees “observed that a certain amount of penetration of the fleet (perhaps 20 to 30 percent) is needed before there are enough data to do the analysis required for regulation.”
In addition, the interaction between software engineering and mechanical engineering is very new to regulators, and this interaction in automated driving systems is far more complex than anything seen in the advanced driver assistance systems available on the market today. Fortunately, savvy regulators appear to understand this challenge, with one government official interviewed in the RAND report saying, “A premature imposition of operational standards could be counterproductive or ineffective. . . . It is better to not establish performance measures up front—it is better if that happens through a sort of evolutionary process.”
The call by some activists for the federal government to impose detailed regulations prior to the development of technical standards and test procedures not only contradicts longstanding federal policy and practice; it would also short-circuit the efficient development of these needed technical standards and delay the realization of potential safety gains. Policymakers would be wise to reject these misguided and overly precautionary appeals to safety and allow standardization efforts to continue unfettered.
For more on this topic, please see Reason Foundation’s recent policy brief, “Challenges and Opportunities for Federal Automated Vehicle Policy,” which aims to provide guidance to policymakers as they work to develop a pro-innovation national framework for automated vehicles.
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