Showing posts with label policy. Show all posts
Showing posts with label policy. Show all posts

Friday, December 29, 2023

My Automated Vehicle Safety Prediction for 2024

 My 2024 AV industry prediction starts with a slide show with a sampling of the many fails for automated vehicles in 2023 (primarily Cruise, Waymo, Tesla). Yes, some hopeful progress in many regards. But so very many fails.



At a higher level, the real event was a catastrophic failure of the industry's strategy of relentlessly shouting as loud as they can "Hey, get off our case, we're busy saving lives here!" The industry' lobbyists and spin doctors can only get so much mileage out of that strategy, and it turns out it is far less (by a factor of 10+) than the miles required to get statistical validity on a claim of reducing fatality rates.

My big prediction for 2024 is the industry (if it is to succeed) will get a more enlightened strategy for both deployment criterion and messaging. Sure, on a technical basis, indeed it needs to be safer than comparable human driver outcomes.

But on a public-facing basis it needs to optimize for fewer embarrassments like the 30 photos-with-stories in this slide show. The whole industry needs to pivot into this priority. The Cruise debacle of the last few months proved (once again; remember Uber ATG?) that it only takes one company doing one ill-advised thing to hurt the entire industry.

I guess the previous plan was they would be "done" faster than people could get upset about the growing pains. Fait accompli. That was predictably incorrect. Time for a new plan.

Wednesday, October 25, 2023

My Talk at a SF Transportation Authority Board meeting

On October 24th I had the privilege of testifying at a San Francisco CTA board meeting regarding autonomous vehicle safety. The session started with SFCTA and SFMTA describing the challenges they have had with robotaxis, my talk, and then a series of Q&As about additional relevant topics. The robotaxi companies were invited to participate but declined. The news of the CA DMV suspension of Cruise permits broke as the hearing was starting, adding some additional context to the hearing.

We have all heard the hype and marketing from the robotaxi companies. This event gave air time to the challenges faced by cities that must be resolved for this technology to succeed at scale.

  • Information about the event:  (link)
  • Full hearing video:  (link
    • Start at 33:48 (click on item 11 in the index to fast forward to that point) for the full segment including SFCTA and SFDMV.
    • My talk starts at 1:10:25
  • My talk only, live recording:  Youtube | Archive.org
  • Slides for my talk (link to acrobat)
The robotaxi companies were invited, but declined to participate in this event. You can see what they have to say from the transcript of a CPUC status conference held on August 7, 2023: https://docs.cpuc.ca.gov/PublishedDocs/Efile/G000/M517/K407/517407815.PDF

Direct link to YouTube talk:





Saturday, August 26, 2023

Autonomous Vehicle State Policy Issues (Talk Video)

The commercial deployment of robotaxis in San Francisco has made it apparent many issues remain to be resolved regarding the regulation and governance of autonomous vehicle technology at the state and local levels. This talk is directed at state and local stakeholders who are considering how to set policies and regulations governing this technology.

Topics:

  • Getting past Automated Vehicle (AV) safety rhetoric
  • AV safety in a nutshell
    • Safe as a human driver on average
    • Avoiding risk transfer to vulnerable populations
    • Avoiding negligent computer driving
    • Conforming to industry consensus safety standards
    • Addressing other ethical & equity concerns
  • Policy points:
    • Societal benefits
    • Public road testing
    • Municipal preemption
    • SAE Level 2/2+/3 issues
    • Federal vs. state regulation
    • Other policy issues
  • Revisiting common myths


Washington State policy meeting in which I give this talk and answer questions: https://avworkgroupwa.org/committee-meeting/executive-committee-meeting-15




Thursday, July 27, 2023

AV Safety Claims and More on My Congressional Testimony

I recently had the privilege of testifying before the US House E&C committee on self-driving car safety. You can see the materials here:

A venue like this does not offer the best forum for nuance. In particular, one can make a precise statement for a reason and have that statement misunderstood (because there is limited time to explain), or misconstrued. The result can be talking past each other for reasons ranging from simple misunderstanding, to ideological differences, to the other side needing to show they are right regardless of the counter-arguments. I do not attempt to cover all topics here; just ones that feel like they could use some more discussion. (See my written testimony for the full list of topics.)

The venue also requires expressing opinions about the best path forward, which can legitimately have different views. I happen to believe that setting up a requirement to follow safety standards is our best bet to be competitive long term with international competitors (who end up having that same requirement). Others disagree.

In this blog I have the luxury of spending some time on some areas that could not be covered with as much nuance/detail in the official proceedings.

US House E&C Hearing on July 26, 2023


Claims that AVs are already safe are premature

Ultimately AVs will win or lose based on public trust. I believe that making overly aggressive claims about safety degrade that trust.

The AV companies are busy messaging that they have already proven are they are better than human drivers, and framing it as a discussion of fatality rates. In other words, they are declaring victory on public road safety in terms of reducing road fatalities. But the data analysis does not support that they are reducing fatalities, and it is still not really clear what the crash/injury rate outcomes are.

Their messaging amounts to 40,000 Americans die on roads every year. We have proven we are safer. Delaying us will kill people.   (Where "us" is the AV industry.)  (Cruise: "Humans are terrible drivers" and computers "never drive distracted, drowsy, or drunk"Cruise has also published some bar graphs of unclear meaning, because the baseline data and details are not public, and the bars selected tell only part of the story (e.g., "collision with meaningful risk of injury" instead of injuries when we know they have already had a multi-injury crash, which therefore undercounts injuries; and only collisions with "primary contribution" when we know they were partially at fault for that multi-injury crash, even if not at "primary" fault.) I have not seen Cruise explicitly say they have reduced fatalities (they say they "are on track to far exceed this projected safety benefit"), but the implied message of declaring victory on safety is quite clear from them ("our driverless AVs have outperformed the average human drier in San Francisco by a large margin.")

Other messaging might be based on reasonable data analysis that is extended to conclusions that go beyond the available data. Waymo: "the Waymo Driver is already reducing traffic injuries and fatalities" -- where the fatality rate is an early estimate, and the serious injury rate numbers are small enough to still be in the data collection phase.  Did I say their report is wrong? I did not. I said that the marketing claims being made are unsupported. If they claimed "our modeling projects we are reducing traffic injuries and shows us on track for reducing fatalities" then that might well be a reasonable claim. But it is not the claim they are making. I note their academic-style papers do a much more rigorous job of stating claims than their marketing material. So this is a matter of overly-aggressive marketing.

It is premature to declare victory. (Did I say the claim of reduced fatalities is definitely false? No. I said it is premature to make that claim. In other words, nobody knows how this will turn out.)

Waymo and Cruise have 1 to 3 million miles each without a driver. Mean time between human driver fatal crashes is ballpark 100 Million miles (details and nuances, but we know human drivers -- including the drunks -- can do this on US public roads in a good year). So at a few million miles there is insufficient experience to know how fatalities will actually turn out.

We are much further away from the data it will take to understand fatalities, which ranges from 300 million to 1 billion miles for a high statistical confidence. A single fatality by any AV company in the next year or so would likely prove that AVs are not safe enough, but we don't know if that will happen.

Missy Cummings has recent results that shows that Waymo has about 4x more non-fatal crashes on non-interstate roads than average human drivers (also on non-interstate roads) -- and Cruise has about 8x more. However, these crash rates are similar to Lyft and Uber in California.  (There is actual research backing up that statement that will be published in due course.)

Also, even if one company shows it is safe enough, that does not automatically make other companies safe. We've already seen differences between Waymo (no injury crashes) and Cruise (a multi-injury crash). Whether that is just bad luck or representative still takes more data. Industry messaging that amounts to "Waymo is safe therefore all AVs are safe" is also problematic, especially if it claims victory on fatality rates.

The reality is that both Waymo and Cruise are using statistical models of varying degrees of sophistication to predict their safety outcomes. Predictions can be wrong. In safety predictions often are wrong for companies with poor safety cultures or who decide not to follow industry safety standards -- but we don't find out until the catastrophic failure makes the news. We can hope that won't happen here, but it is hope, not time for a victory dance.

Summary: Companies are predicting they will reduce fatalities. That is not the same as actually proving it. There is a long way to run here, and the only thing I am sure is there will be surprises. Perhaps in a year we'll have enough data to get some more clarity about property damage and injury crashes, but only for companies that want to be transparent about their data.  It will be even longer to show that the fatality rate is on a par with human drivers. If bad news arrives, it will come sooner. We should not make policy assuming they are safer.

Blame and AV safety

Blaming someone does not improve safety if it deflects the need to make a safety improvement. In particular, saying that a crash was not the fault of an AV company is irrelevant to measuring and improving safety. Much of road safety comes not from being blameless, but rather for compensating for mistakes, infrastructure faults, and other hazards not one's own fault. 

Any emphasis on metrics that emphasizes "but it was not mostly our fault" is about public relations, not about safety.  I guess PR is fine for investors, but baking that into a safety management system means lost opportunities to improve safety. That is not the behavior appropriate for any company who claims safety is their most important priority.  If a company wants to publish both "crashes" and "at fault crashes" then I guess OK (although "at fault" should include partially at fault, not 49% at fault rounds down to 0% at fault). But publishing only "at fault" crashes is about publicity, not about safety transparency. (Even worse is lobbying that only "at fault" crashes should be reported in data collection.)

On the other hand, it is important to hold AV companies accountable for safety, just as we hold human drivers accountable. A computer driver should have the same duty of care as a human driver on public roads. This is not formally the situation now, and this part of tort law will take a lot of cases to resolve, wasting a lot of time and resources. The manufacturer should be the responsible party for any negligent driving (i.e., driving behavior that would be negligent if a human driver were to do it) by their computer driver. Not the owner, and not the operator, because neither has the ability to design and validate the computer driver's behavior. This aspect of blame will use tort law in its primary role: to put pressure on the responsible party to avoid negligent driving behavior. The same rules should apply to human and computer drivers.

There is a nuanced issue regarding liability here. Companies seem to want to restrict their exposure to being only product liability, and evade tort law. However, if a computer driver runs a red light, that should be treated exactly as a human driver negligence situation. There should be no need to reverse engineer a huge neural network to prove a specific design defect (product liability) -- the fact of running a red light should be the basis for making a claim based on negligent behavior alone (tort law) without having the burden to prove a product defect. Product liability is more expensive and more difficult to pursue. The emphasis should be on using tort law when possible, and product liability only as a secondary path. That will keep costs down and make deserved compensation more accessible on the same basis it is for human driver negligence.

Also, aggressively blaming others rather than saying at the very least "we could have helped avoid this crash even if other driver is assigned blame" degrades trust.

Summary: Statistics that incorporate blame impair transparency. However, it is helpful for tort law to hold the manufacturers accountable for negligent behavior by computer drivers. And you would think computer drivers should have near-zero negligent driving rates? Insisting on product liability rather than tort law is a way for manufacturers to decrease their accountability for computer driver problems, harming the ability other road users to seek justified compensation if harmed.

Level 2/2+:

All this attention to AVs is distracting the discussion from a much bigger and more pressing economic and safety issue: auto-pilot systems and the like. The need to regulate those systems is much more urgent from a societal point of view. But it's not the discussion because the auto industry has already gotten itself a situation with no regulation other than a data reporting requirement and the occasional (perhaps after many years) recall.

Driver monitoring effectiveness and designing a human/computer interaction approach that does not turn human drivers into moral crumple zones needs a lot more attention. It will take a long time for NHTSA to address this beyond doing recalls for the more egregious issues. Tort law (holding the computer driver accountable when it is steering) seems the only viable way to put some guard rails in place in the near- to mid-term.

Opinion: Level 2/2+ is what matters for the car industry now for both safety and economic benefits. AVs are still a longer term bet. 

Don't sell on safety:

Companies should not sell solving the 40K/year fatality problem. There are many other technologies that can make a much quicker difference in that area. And social change for that matter. If what we want is better road safety, investing tens of billions of dollars in robotaxi technology is one of the least economically efficient ways to do this. Instead we could improve active safety systems, encourage a switch to safer mass transit, press harder for social change on impaired/distracted driving, and so on. While one hopes this will long term help with fatalities, this is simply the wrong battle for the industry to try to fight with this technology for at least a decade. (Even if the perfect robotaxi were invented today -- which we are a long way from -- it would take many years to see a big drop in fatalities due to the time to turn over the automotive fleet that has an average age of about 12 years.)

Companies should sell on economic benefit, being better for cities, being better for consumers, transportation equity, and so on -- while not creating safety issues. Safety promises should simply indicate they are doing no harm. This is much easier to show, assuming it is true. And it does not set the industry up for collapse when the next (remember Uber ATG?) fatality eventually arrives.

The issue is that any statement about reducing fatalities is a prediction, not a conclusion. I would hope  that car companies would not release a driverless car onto public roads unless they can predict it is safer than a human driver. They should disclose that argument in a transparent way. But it is a prediction, not a certainty. It will take years to prove. Why pick a fight that is so difficult when there is really no need to do so? 

A smarter way to explain to the public how they are ensuring a safe and responsible release is to use an approach such as:
  1. Follow industry safety standards to set a reasonable expectation of safe deployment and publicly disclose independent conformance checks.
  2. Establish metrics that will be used to prove safety in advance (not cherry-picked after the fact).
  3. Transparent monthly reports of those metric outcome vs. goals
  4. Show that issues identified are resolved vs. continuing to scale up despite problems. Problems includes not only crashes, but also negative externalities on other road users
  5. Publish lessons learned in a generic way
  6. Show public benefit is being delivered beyond safety, again with periodic metric publications.
Three principles for safety, all of which are a problem with the industry's current adversarial approach to regulatory oversight, are:
  1. Transparency
  2. Accountability
  3. Independent oversight
It is not only that you need to do those things to actually get safety. It is also that these things build trust.

Other key points:

  • Any person or organization who promotes the "human drivers are bad, so computers will be safe " and/or the "94% of crashes are caused by human error" talking points should be presumptively considered an unreliable source of information. At this point I feel those are propaganda points. Any organization saying that Safety is their #1 priority should know better.
  • The main challenge to the industry is not regulations -- it is the ability to build reliable, safe vehicles that scale up in the face of the complexity of the real world. Expectations of exponential numbers of cars deploying any time soon seem unrealistic. The current industry city-by-city approach is likely to continue to grind away for years to come. Being realistic about this will avoid pressure to make overly aggressive deployments that compromise safety.
  • In other industries (e.g., aviation, rail) following their own industry standards is an essential part of assuring safety. The car companies should be required to follow their standards too (e.g., ISO 26262, ISO 21448, UL 4600, ISO/SAE 21434, perhaps ISO TS 5083 when we find out what is in it). This varies across companies, with some companies being very clearly against following those standards.
  • There is already a regulatory framework, written by the previous administration. This gives us an existing process with an existing potential bipartisan starting point to move the discussion forward instead of starting from scratch with rule making. That framework includes a significant shift in government policy to require the industry to follow its own consensus safety standards. My understanding is that US Government policy is to use such standards whenever feasible. It is time for US DOT to get with the program here (as they proposed to do several years ago -- but stalled ever since).
  • Absolute municipal and state preemption are a problem, especially for "performance" aspects of a computer driver:
    • This leaves states and localities prevented from protecting their constituents (if they choose to do so) while the Federal Government is still working on AV regulations
    • Even after there are federal regulations, state and local governments need to be able to create and enforce traffic laws, rules of the road, and hold computer drivers accountable (e.g., issue and revoke licenses based on factors such as computer driver negligence)
    • In the end, the Federal Government should regulate the ability of equipment to follow whatever road rules are in place. States and localities should be able to set behavioral rules for road use and enforce compliance for computer drivers without the Federal Government subsuming that traditional State/Local ability to adapt traffic rules to local conditions.
  • Do you remember how ride hail networks were supposed to solve the transportation equity problem? Didn't really happen, did it? Forced arbitration was a part of that outcome, especially for the disabled. We need to make sure that the AV story has a better ending by avoiding forced arbitration being imposed on road users. It is even possible that taking one ride hail ride might force you into arbitration if you are later hurt as a pedestrian by a car from that company (depends on the contract language -- the one you clicked without really reading or understanding even if you did read it). Other aspects of equity matter too, such as equity in exposing vulnerable populations to the risks of public road testing.
  • There are numerous other points summarized after the end of my written narrative that also matter, covering safety technology, jobs/economic impact, liability, data reporting, regulating safety, avoiding complete preemption, and debunking industry-promoted myths.
  • There is a Q&A at the end of my testimony where I have the time to give more robust answers to some of the questions I was asked, and more.

Last update 7/27/2023

Sunday, July 16, 2023

AV Safety and the False Dilemma Fallacy

The current AV company messaging strategy is a classic case of a false dilemma fallacy. They frame the situation as a choice between continued human drivers killing people (without statistical context) vs. immature robotaxis who don't drink and drive (but make other mistakes). (Wikipedia: False dilemma)


The recent Cruise ad in particular is a plainly ridiculous doubling-down on the industry's long discredited propaganda playbook.

Cruise NY Times ad: https://twitter.com/kvogt/status/1679517290847694848


Analysis of AV industry playbook: https://www.eetimes.com/autonomous-vehicle-myths-the-dirty-dozen/


A more reasonable message would be cities need robotaxis for <reasons> and robotaxi companies will use <defined, balanced metrics, stated in advance rather than cherry picked later> to show they are no worse than human drivers during development, with monthly report card disclosures. Improved safety comes later -- we all hope.


Here is where things really stand:

  • It is too early to know whether current robotaxi technology is safer than human drivers for fatalities. The industry is stringing us along hoping they can show they are safe over time (starting now, but not really there yet).
  • Non-autonomous technology (AEB) is making far more of a contribution right now -- but is missing from the false dilemma.
  • Public transit (much safer) also not in the discussion.
  • Improving road safety (speed limits, traffic calming, etc.) also not in the discussion. Also missing are specific pedestrian and cyclist safety improvements. While we're at it, seat belts, drunk driving, and motorcycle safety measures.
  • The messaging from both sides (parts of the SF govt and especially Cruise) on crashes does not address factors required for a reasonable comparison. (ODD, baseline driver population, etc.)
  • It is clear that vehicles from both Waymo and Cruise are creating public road disruption. There is no excuse for impeding emergency responders just to get "Look Ma, No Driver!!" optics.
  • The technology can be advanced by continuing to test while having human drivers or in-car valets (employee in the front passenger seat) to mitigate problems. Their Safety Management System should include a step of adding/removing in-car vehicle supervisors until issues that cause public disruption are shown to be resolved in deployment.
  • Cruise in particular needs to get more diligent about pre-deployment testing. There is simply no excuse for rear-ending a Muni bus due to a software defect in an uncrewed vehicle that occurred in a pretty normal situation. Waymo isn't perfect, but their failures are more at the edge.
  • The public outrage is entirely self-inflicted by companies due to their exploitation of the municipal preemption clause in state-level regulations rather than being responsible road users. Playing the "we should forgive their drivers who are still learning" card has worn out its welcome.


Some might want to point out that some companies are worse actors than others, but all the companies have their issues. (For example, good work by the Waymo safety team is hurt by their government relations breathless safety hype messaging.)


And the reality is that a crash or adverse news for one company hurts them all.


Tuesday, March 21, 2023

A Liability-Based Regulatory Framework for Vehicle Automation Technology

State liability laws might be the way out of the automated vehicle regulatory dilemma. From phantom braking to reckless public road testing to permitting using human drivers as moral crumple zones, vehicle automation regulation is a hot mess. States are busy creating absurd laws that assign safety responsibility to a non-legal-person computer, while the best the feds can do under the circumstances is play recall whack-a-mole with unsafe features that are deployed faster than they can investigate.

What has become clear is that attempting to regulate the technology directly is not working out. In the long term it will have to be done, but we will likely need to see fundamental changes at US DOT before we see viable regulatory approaches to automated vehicles. (As a start, they need to abandon the use of SAE Levels for regulatory purposes.) That process will take years, and if history is any guide, one or more horrific tragedies before things settle out. Meanwhile, as companies aggressively exploit the "Level 2 loophole" it is the wild west on public roads. Various companies are taking safety with different levels of seriousness, but there is a dramatic lack of transparency and accountability across the industry that will only get worse with time.


As a short- to mid-term approach we should revisit how liability laws work at the state level to buy time to let the technology mature while avoiding needless harm to constituents. There are three fundamental things that have changed that make the current tort system unworkable in practice for automated vehicle technology:

#1: Machine learning-based technology is inherently unsuitable to traditional software safety analysis. The current legal system which puts the burden of showing technology is defective on victims is simply not viable when even the engineers who designed a system can't necessarily explain why the computer driver did what it did.

#2: Asymmetric access to information makes it easy for car companies to know what happened in a crash (or even if automated driving was activated), but it is very difficult for victims to access, much less interpret such information.

#3: The litigation cost of pursuing a claim against software with non-deterministic defects that require source code analysis is huge, depriving all but the largest cases from having an effective ability to prove a product defect claim, if one is justified.


In response to these realities, a (rebuttable) presumption of liability and burden of proof should be shifted to manufacturers in situations for which it is unreasonable to expect a civilian human driver to be able to ensure safety. The attached summary sketches an approach, with more detail to come.


Read the one-pager policy summary here: https://archive.org/details/2023-03-av-liability-one-pager-published-v-1-00



Sunday, November 13, 2022

Book: How Safe is Safe Enough? Measuring and Predicting Autonomous Vehicle Safety

How Safe Is Safe Enough for Autonomous Vehicles? 
The Book


The most pressing question regarding autonomous vehicles is: will they be safe enough? The usual metric of "at least as safe as a human driver" is more complex than it might seem. Which human driver, under what conditions? And are fewer total fatalities OK even if it means more pedestrians die? Who gets to decide what safe enough really means when billions of dollars are on the line? And how will anyone really know the outcome will be as safe as it needs to be when the technology initially deploys without a safety driver?

This book is written by an internationally known expert with more than 25 years of experience in self-driving car safety. It covers terminology, autonomous vehicle (AV) safety challenges, risk acceptance frameworks, what people mean by "safe," setting an acceptable safety goal, measuring safety, safety cases, safety performance indicators, deciding when to deploy, and ethical AV deployment. The emphasis is not on how to build machine learning based systems, but rather on how to measure whether the result will be acceptably safe for real-world deployment. Written for engineers, policy stakeholders, and technology enthusiasts, this book tells you how to figure out what "safe enough" really means, and provides a framework for knowing that an autonomous vehicle is ready to deploy safely.

Currently available for purchase from Amazon, with international distribution via their print-on-demand network. (See country-specific distribution list below.)

See bottom of this post for e-book information, from sources other than Amazon, as well as other distributors for the printed book.

Media coverage and bonus content:

Chapters:

  1. Introduction
  2. Terminology and challenges
  3. Risk Acceptance Frameworks
  4. What people mean by "safe"
  5. Setting an acceptable safety goal
  6. Measuring safety
  7. Safety cases
  8. Applying SPIs in practice
  9. Deciding when to deploy
  10. Ethical AV deployment
  11. Conclusions
368 pages.
635 footnotes.
On-line clickable link list for the footnotes here: https://users.ece.cmu.edu/~koopman/SafeEnough/

Koopman, P., How Safe Is Safe Enough? Measuring and Predicting Autonomous Vehicle Safety, September 2022.
ISBN: 9798846251243 Trade Paperback
ISBN: 9798848273397 Hardcover   (available only in marketplaces supported by Amazon)

Also see my other recent book: The UL 4600 Guidebook

For those asking about distribution -- it is served by the Amazon publishing network. Expanded distribution is selected, so other distributors might pick it up in 6-8 weeks to serve additional countries (e.g., India) or non-Amazon booksellers, especially in US and UK. How that goes is beyond my control, but in principle a bookstore anywhere should be able to order it by about mid-November 2022. Alternately, you can order it direct from Amazon in the closest one of these countries for international delivery: US, UK, DE, FR, ES, IT, NL, PL, SE, JP, CA, AU.


You can also buy it from some Amazon country web sites via distributors. A notable example is:

Your local bookstore should also be able to order it through their US or UK distributor.

E-book available from distributors as they pick it up over time: 

Tuesday, February 11, 2020

Positive Trust Balance for Self Driving Car Deployment

By Philip Koopman and Michael Wagner, Edge Case Research

Self-driving cars promise improved road safety. But every publicized incident chips away at confidence in the industry’s ability to deliver on this promise, with zero-crash nirvana nowhere in sight. We need a way to balance long term promise vs. near term risk when deciding that this technology is ready for deployment. A “positive trust balance” approach provides a framework for making a responsible deployment decision by combining testing, engineering rigor, operational feedback, and transparent safety culture.


MILES AND DISENGAGEMENTS AREN’T ENOUGH

Too often, discussions about why the public should believe a particular self-driving car platform is well designed center around number of miles driven. Simply measuring the number of miles driven has a host of problems, such as distinguishing “easy” from “hard” miles and ensuring that miles driven are representative of real world operations. That aside, accumulating billions of road miles to demonstrate approximate parity to human drivers is an infeasible testing goal. Simulation helps, but still leaves unresolved questions about including enough edge cases that pose problems for deployment at scale.

By the time a self-driving car design is ready to deploy, the rate of potentially dangerous disengagements and incidents seen in on-road testing should approach zero. But that isn’t enough to prove safety. For example, a hypothetical ten million on-road test miles with no substantive incidents would still be a hundred times too little to prove that a vehicle is as safe as a typical human driver. So getting to a point that dangerous events are too rare to measure is only a first step.

In fact, competent human drivers are so good that there is no practical way to measure that a newly developed self-driving car has a suitably low fatality rate. This should not be news. We don’t fly new aircraft designs for billions of hours before deployment to measure the crash rate. Instead, we count on a combination of thorough testing, good engineering, and safety culture. Self-driving cars typically rely on machine learning to sense the world around them, so we will also need to add significant feedback from vehicles operating in the field to plug inevitable gaps in training data.


POSITIVE TRUST BALANCE

The self-driving car industry is invested in achieving a “positive risk balance” of being safer than a human driver. And years from now actuarial data will tell us if we succeeded. But there will be significant uncertainty about risk when it’s time to deploy. So we’ll need to trust development and deployment organizations to be doing the right things to minimize and manage that risk.

To be sure, developers already do better than brute force mileage accumulation. Simulations backed up by comprehensive scenario catalogs ensure that common cases are covered. Human copilots and data triage pipelines flag questionable self-driving behavior, providing additional feedback. But those approaches have their limits.

Rather than relying solely on testing, other industries use safety standards to ensure appropriate engineering rigor. While traditional safety standards were never intended to address self-driving aspects of these vehicles, new standards such as Underwriters Laboratories 4600 and ISO/PAS 21448 are emerging to set the bar on engineering rigor and best practices for self-driving car technology.

The bad news is that nobody knows how to prove that machine learning based technology will actually be safe. Although we are developing best practices, when deploying a self-driving car we’ll only know whether it is apparently safe, and not whether it is actually as safe as a human driver. Going past that requires real world experience at scale.

Deploying novel self-driving car technology without undue public risk will involve being able to explain why it is socially responsible to operate these systems in specific operational design domains. This requires addressing all of the following points:

Is the technology as safe as we can measure? This doesn’t mean it will be perfect when deployed. Rather, at some point we will have reached the limits of viable simulation and testing.

Has sufficient engineering rigor been applied? This doesn’t mean perfection. Nonetheless, some objective process such as establishing conformance to sufficiently rigorous engineering standards that go beyond testing is essential.

Is a robust feedback mechanism used to learn from real world experience? There must be proactive, continual risk management over the life of each vehicle based on extensive field data collection and analysis.

Is there a transparent safety culture? Transparency is required in evolving robust engineering standards, evaluating that best practices are followed, and ensuring that field feedback actually improves safety. A proactive, robust safety culture is essential. So is building trust with the public over time.

Applying these principles will potentially change how we engineer, regulate, and litigate automotive safety. Nonetheless, the industry will be in a much better place when the next adverse news event occurs if their figurative public trust account has a positive balance.

Philip Koopman is the CTO of Edge Case Research and an expert in autonomous vehicle safety. Including his role as a faculty member at Carnegie Mellon University, Koopman has been helping government, commercial and academic self-driving developers improve safety for over 20 years. He is a principal contributor to the Underwriters Laboratories 4600 safety standard.

Michael Wagner is the CEO of Edge Case Research. He started working on autonomy at Carnegie Mellon over 20 years ago.


(Original post here:  https://medium.com/@pr_97195/positive-trust-balance-for-self-driving-car-deployment-ff3f04a7ef93)

Tuesday, May 28, 2019

Ethical Problems That Matter for Self Driving Cars

It's time to get past the irrelevant Trolley Problem and talk about ethical issues that actually matter in the real world of self driving cars.  Here's a starter list involving public road testing, human driver responsibilities, safety confidence, and grappling with how safe is safe enough.


  • Public Road Testing. Public road testing clearly puts non-participants such at pedestrians at risk. Is it OK to test on unconsenting human subjects? If the government hasn't given explicit permission to road test in a particular location, arguably that is what is (or has been) happening. An argument that simply having a "safety driver" mitigates risk is clearly insufficient based on the tragic fatality in Tempe AZ last year. 
  • Expecting Human Drivers to be Super-Human. High-end driver assistance systems might be asking the impossible of human drivers. Simply warning the driver that (s)he is responsible for vehicle safety doesn't change the well known fact that humans struggle to supervise high-end autonomy effectively, and that humans are prone to abusing highly automated systems. This gives way to questions such as:
    • At what point is it unethical to hold drivers accountable for tasks that require what amount to super-human abilities and performance?
    • Are there viable ethical approaches to solving this problem? For example, if a human unconsciously learns how to game a driver monitoring system (e.g., via falling asleep with eyes open -- yes, that is a thing) should that still be the human driver's fault if a crash occurs?
    • Is it OK to deploy technology that will result in drivers being punished for not being super-human if result is that the total death rate declines?
  • Confidence in Safety Before Deployment.  There is work that advocates even slightly better than a human is acceptable (https://www.rand.org/blog/articles/2017/11/why-waiting-for-perfect-autonomous-vehicles-may-cost-lives.html). But there isn't a lot of discussion about the next level of what that really means. Important ethical sub-topics include:
    • Who decides when a vehicle is safe enough to deploy? Should that decision be made by a company on its own, or subject to external checks and balances? Is it OK for a company to deploy a vehicle they think is safe based just on subjective criteria alone: "we're smart, we worked hard, and we're convinced this will save lives"
    • What confidence is required for the actual prediction of casualties from the technology? If you are only statistically 20% confident that your self-driving car will be no more dangerous than a human driver, is that enough?
    • Should limited government resources that could be used for addressing known road safety issues (drunk driving, driving too fast for conditions, lack of seat belt use, distracted driving) be diverted to support self-driving vehicle initiatives using an argument of potential public safety improvement?
  • How Safe is Safe Enough? Even if we understand the relationship between an aggregate safety goal and self-driving car technology, where do we set the safety knob?  How will the following issues affect this?
    • Will risk homeostatis apply? There is an argument that there will be pressure to turn up the speed/traffic volume dials on self-driving cars to increase permissiveness and traffic flow until the same risk as manual driving is reached. (Think more capable cars resulting in crazier roads with the same net injury and fatality rates.)
    • Is it OK to deploy initially with a higher expected death rate than human drivers under an assumption that systems will improve over time, long term reducing the total number of deaths?  (And is it OK for this improvement to be assumed rather than proven to be likely?)
    • What redistribution of demographics for victims is OK? If fewer passengers die but more pedestrians die, is that OK if net death rate is the same? Is is OK if deaths disproportionately occur to specific sub-populations? Did any evaluation of safety before deployment account for these possibilities?
I don't purport to have the definitive answers to any of these problems (except a proposal for road testing safety, cited above). And it might be that some of these problems are more or less answered. The point is that there is so much important, relevant ethical work to be done that people shouldn't be wasting their time on trying to apply the Trolley Problem to AVs. I encourage follow-ups with pointers to relevant work.

If you're still wondering about Trolley-esque situations, see this podcast and the corresponding paper. The short version from the abstract of that paper: Trolley problems are "too contrived to be of practical use, are an inappropriate method for making decisions on issues of safety, and should not be used to inform engineering or policy." In general, it should be incredibly rare for a safely designed self-driving car to get into a no-win situation, and if it does happen they aren't going to have information about the victims and/or aren't going to have control authority to actually behave as suggested in the experiments any time soon, if ever.

Here are some links to more about applying ethics to technical systems in general (@IEEESSIT) and autonomy in particular (https://ethicsinaction.ieee.org/), as well as the IEEE P7000 standard series (https://www.standardsuniversity.org/e-magazine/march-2017/ethically-aligned-standards-a-model-for-the-future/).


Monday, November 26, 2018

FiveAI Report on Autonomous Vehicle Safety Certification

FiveAI has published an autonomous vehicle safety approach that includes independent verification, transparency, and data sharing. (I provided inputs to the @_FiveAI  authors.)

Here is a pointer to the summary on Medium
https://medium.com/@_FiveAI/we-need-an-industry-wide-safety-certification-framework-for-autonomous-vehicles-fiveai-publishes-1139dacd5a8c

It's worth jumping through the registration hoop to read the full version.
https://five.ai/certificationpaper


Tuesday, September 18, 2018

Automotive Safety Practices vs. Accepted Principles (SAFECOMP paper)

I'm presenting this paper at SAFECOMP this today

2018 SAFECOMP Paper Preprint

Abstract. This paper documents the state of automotive computer-based system safety practices based on experiences with unintended acceleration litigation spanning multiple vehicle makers. There is a wide gulf between some observed automotive practices and established principles for safety critical system engineering. While some companies strive to do better, at least some car makers in the 2002-2010 era took a test-centric approach to safety that discounted nonreproducible and “unrealistic” faults, instead blaming driver error for mishaps. Regulators still follow policies from the pre-software safety assurance era. Eight general areas of contrast between accepted safety principles and observed automotive safety practices are identified. While the advent of ISO 26262 promises some progress, deployment of highly autonomous vehicles in a nonregulatory environment threatens to undermine safety engineering rigor.

See the full paper here:
https://users.ece.cmu.edu/~koopman/pubs/koopman18_safecomp.pdf

Note that there is some pretty interesting stuff to be seen by following the links in the paper reference section.
Also see the expanded list of (potentially) deadly automotive defects.

Here are the accompanying slides:  https://users.ece.cmu.edu/~koopman/pubs/koopman18_safecomp_slides.pdf







Wednesday, September 12, 2018

Victoria Australia Is Winning the Race to ADS Testing Safety Regulations

Victoria Australia has just issued new guidelines regarding Automated Driving System (ADS) testing.  These should be required reading for anyone doing on-road testing elsewhere in the world. There is just too much good stuff here to miss.  And, the guidelines are accompanied by actual laws that are designed to make autonomy testing safe.

A look through the regulations and guidelines shows that there is a lot to like. The most intriguing points I noticed were:
  • It provides essentially unlimited technical flexibility to the companies building the ADS vehicles while still providing a way to ensure safety. The approach is a simple two-parter:
    1. The testing permit holders have to explain why they will be safe via a safety management plan.
    2. If the vehicle testing doesn't follow the safety management plan or acts unsafely on the roads, the testing permit can be revoked.
  • The permit holder rather than the vehicle supervisor (a.k.a. "safety driver" in the US) is liable when operating in autonomous mode.  In other words, if the safety driver fails to avoid a mishap, liability rests with the company running the tests, not the safety driver. That sounds like an excellent way to avoid a hypothetical strategy of companies using safety drivers as scapegoats (or expendable liability shields) during testing.
  • The permitting process requires a description of ODD/OEDR factors including not just geofencing, but also weather, lighting, infrastructure requirements, and types of other road users that could be encountered.
  • The regulators have broad, sweeping powers to inspect, assess, require tests, and in general do the right thing to ensure that on-road testing is safe. For example, a permit can be denied or revoked if the safety plan is inadequate or not being followed.
There are many other interesting and on-target discussions in the guidelines.  They include the need to reduce risk as low as reasonably practicable (ALARP); accounting for the Australian road safety approach of: safe speeds, safe roads, safe vehicles, safe people during testing; transition issues between ADS and supervisor; the need to drive in a predictable way to interact safely with human drivers; and a multi-page list of issues to be considered by the safety plan. There is also a list of other laws that come into play.

Here are some pointers for those who want to look further.
There are some legal back stories at work here as well. For example, it seems that under previous law a passenger in an ADS could have been found responsible for errors made by the ADS, and this has been rectified with the new laws.

The regulations were created according to the following criteria from a 2009 Transportation bill:
  • Transportation system objectives:
    • Social and economic inclusion
    • Economic prosperity
    • Environmental sustainability
    • Integration of transport and land use
    • Efficiency, coordination and reliability
    • Safety and health and well being
  •  Decision making principles:
    • Principle of integrated decision making
    • Principle of triple bottom line assessment
    • Principle of equity
    • Principle of the transport system user perspective
    • Precautionary principle
    • Principle of stakeholder engagement and community participation
    • Principle of transparency. 
(The principle of transparency is my personal favorite.)

Here is a list of key features of the Road Safety (Automated Vehicles) Regulations 2018:

  1. The purpose of an ADS permits scheme (see regulation 5):
    • For trials of automated driving systems in automated mode of public roads
    • To enable a road authority to monitor and  manage the use and impacts of the automated driving system on a highway
    • To enable VicRoads to perform its functions under the Act and the Transport Integration Act
  2. The permit scheme requires the applicant to prepare and maintain a safety management plan that (see regulation 9 (2)):
    • Identifies the safety risks of the ADS trials
    • Identifies the risks to the reliability, security and operation of the automated driving system to be used in the ADS trial
    • Specifies what the applicant will do to eliminate or reduce those risks so far as is reasonably practicable; and
    • Addresses the safety criteria set out in the ADS guidelines
  3. The regulations will require the ADS permit holder to submit a serious incident within 24 hours (see regulations 13 and 19). A serious incident means any:
    • accident
    • speeding, traffic light, give way and level crossing offence
    • theft or carjacking
    • tampering with, unauthorised access to, modification of, or impairment of an automated driving system
    • failure of an automated driving system of an automated vehicle that would impair the reliability, security or operation of that automated driving system.
I hope that US states (and the US DOT) have a look at these materials.  Right now I'd say VicRoads is ahead of the US in the race to comprehensive but reasonable autonomous vehicle safety regulations.

(I would not at all be surprised if there are issues with these regulations that emerge over time. My primary point is that it looks to me like responsible regulation can be done in a way that does not pick technology winners and does not unnecessarily hinder innovation. This looks to be excellent source material for other regions to apply in a way suitable to their circumstances.)