Five Principles for Regulation of highly Automated Vehicles

February 1, 2022


Philip Koopman∗ & William H. Widen**

Providing economic opportunities and jobs is important, but these benefits alone are not an equitable and fair exchange for the use of public highways as a testing ground, and the exposure of the public to an increased risk of harm from highly automated vehicle (HAV) accidents during development. The principles below summarize concrete actions that HAV legislation should include to provide an appropriate balance.

Typeset Acrobat version here:

1. Safety

Operational Safety: commit to a testing and deployment standard for automated driving system (ADS) performance of “substantially better than the average unimpaired human driver (AUHD) rather than the vague “sufficiently safe” criteria currently in use by HAV companies.

Metrics: state the metric(s) used to make the performance comparison between an ADS and the AUHD.

Industry Standards: commitment to follow published professional industry standards appropriate for the type of HAV operation (i.e., testing, trials or deployment) including: SAE J3018, UL 4600, ISO 21448 and ISO 26262, as informed by AVSC00001201911 AVSC Best Practice for safety operator selection, training, and oversight procedures for automated vehicles under test and AVSC0007202107 AVSC Information Report for Adapting a Safety Management System (SMS) for Automated Driving System (ADS) SAE Level 4 and 5 Testing and Evaluation.

Regulatory time-out: allow all regulators (federal, state, and local) to temporarily enjoin HAV operations (including testing) as a response to discrete events which raise safety concerns and to revoke testing permits for significant adverse events as well as for patterns of unsafe HAV operations or operations that violate law.

2. Responsibility for Loss (Compensation)

Duty of Care: Any company or person operating an AV should, by statue, owe the public a non-delegable duty of care for safe operation.

Insurance Levels: Use a required insurance amount not less than the US DOT’s statistical value of a human life ($11.6 million per person in 2020, adjusted annually). Do not allow self-insurance by HAV companies which are not cash flow positive. Establish clear single-risk limits and treatment of multiple injuries/fatalities in a single event, with separate treatment for special cases, such as truck platooning which might be expected to cause greater harm on a per incident basis.

Owner/Occupant Liability: Clarify the liability of an owner/occupant of an HAV for loss caused when an ADS is properly engaged. May an injured party sue the owner/occupant in the absence of negligence and collect against the owner’s insurance policy or are claims limited to ADS designers, manufacturers and upfitters for defects? Explain interaction with negligence claims for maintenance, upgrades, and installation failures.

Single Collection Point for Plaintiffs: Allow a plaintiff to collect from a single responsible defendant in full, with joint and several liability and a right of contribution from other responsible parties (regardless of whether the liability is based in negligence or product defect).

Insurance Policy with Plaintiffs in Position of a Named Insured: Allow plaintiffs to make a claim against HAV company insurance policies as if they were a named insured to facilitate prompt payment of medical bills and other amounts so plaintiffs do not face financial pressure to settle for less than full compensation.

Eliminate Barriers to Collection for Full Damages: As applicable, lift caps on damage collection by potential plaintiffs with lower cost insurance policies, such as limited tort option policies in Pennsylvania.

3. Transparency

Periodic reporting: require timely publication of HAV safety performance, including how actual performance of an HAV compares with promised performance relative to the AUHD.

Crash Data: require timely publication of all crash data and police reports for any incident involving a HAV.

Publicize testing, trials, and deployment plans: a requirement to issue publicly a testing plan prior to commencement of testing, trials or deployment which explain how the HAV company addresses safety, responsibility for loss, transparency, inclusion, and non-discrimination. Allow local regulators to review, comment upon, and approve the testing plan.

Identification of times, manner and locations for testing and trials: requirement to post information about the times and locations for testing and trials so the public understands areas of increased risk.

Don’t Promulgate Myths: advocates for an HAV law, rule or regulation, should not use marketing and outreach materials containing untruthful or misleading statements or material omissions, such as the myth that 94% of serious crashes are caused by human error.

Disclose a Harm Now, Benefits Later Justification for Deployment: If an HAV company plans to deploy HAVs at scale when the technology does not perform substantially better than an AUHD, or its level of performance cannot be determined with reasonable certainty, disclose this fact in the testing plan so the public can evaluate a policy which exposes the public to harms on the promise of future improvements to HAV technology.

4. Inclusion

IEEE 7000: require HAV companies to follow the IEEE 7000 Standard Model Process for Addressing Ethical Concerns procedures to identify all interested parties affected by the testing, trials, and deployment of HAV technology (including emergency service responders, hazardous material transporters, and those in a work zone). Address the concerns of all stakeholders in public plans and with respect to testing, trials, and deployments.

Adaptation to Local Conditions: give municipalities the power to limit HAV operations based on time, manner, and location to account for local conditions (such as preventing truck platooning in certain neighborhoods or driverless trials in school zones; account for local special events; account for recent incidents which present safety concerns); remove blanket pre-emption by state law to allow municipalities to exercise this power.

Review Global Approaches to HAV Regulation: as part of approving any bill, review the recommended approaches to HAV regulation taken in other jurisdictions, such as the joint report of the UK law commissions on automated vehicles, and the EU’s ethics guidelines for the development of trustworthy artificial intelligence.

5. Non-Discrimination:

No Concentrated Operations in Areas of Concern: Municipal review of both public testing and trial plans and the time, manner and locations for testing and trials to ensure that at-risk communities, such as low-income neighborhoods, do not experience a disproportionate increased risk of loss from HAV operations (without mitigating the identified risk) as opposed to other communities not deemed to be at special risk.

Mitigation Strategies: If a need arises to concentrate certain types of testing and trials in an at-risk community, use other means to mitigate the adverse impact of the concentration—such as conducting testing only with an on-board safety driver, use of two safety drivers; or elimination of uncrewed trials.

Special Review of Related Laws: review applicable existing state and local laws to identify situations in which HAV operations (including crashes) might adversely impact low-income and other at-risk persons, such as limited damage collection for low-cost policies, and the difficulty and expense of pursuing a product defect claim given legal complexity and number of possible defendants.

Justice40: situate and harmonize non-discrimination efforts within the broader framework of social justice and equity values, including those contained in the Federal Government’s Justice40 initiative.

∗ Philip Koopman is an Associate Professor of Electrical and Computer Engineering at Carnegie Mellon University, Pittsburgh, Pennsylvania, specializing in autonomous vehicle safety.

** William H. Widen is a Professor at the University of Miami School of Law, Coral Gables, Florida. His current research focuses on laws and regulations relating to autonomous vehicles.


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