Op-Ed About Autonomous Vehicle Safety

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IMPORTANT, MUST BE READ... : Op-Ed About Autonomous Vehicle Safety
Title : Op-Ed About Autonomous Vehicle Safety

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Op-Ed About Autonomous Vehicle Safety

IMPORTANT, MUST BE READ... Yesterday the local paper published my op-ed slice on the DoT's draft policy for autonomous vehicle safety.  In the involvement of starting a to a greater extent than full general populace word most this of import topic, it is reproduced below.  I am working a to a greater extent than comprehensive technical response, as well as I'll post service that hither soon.

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Source:
http://www.post-gazette.com/opinion/Op-Ed/2016/09/30/Safe-self-driving-It-s-not-here-yet/stories/201609300137

Safe self-driving? It’s non hither yet
Influenza A virus subtype H5N1 lot of testing remains earlier self-driving cars should endure widely deployed
Pittsburgh Post-Gazette
September 30, 2016 12:00 AM

By Philip Koopman as well as Michael Wagner

President Barack Obama this calendar month announced a Department of Transportation draft policy on automated-vehicle safety. Hard-working staff at the Department of Transportation, the National Highway Traffic Safety Administration as well as the Volpe National Transportation Systems Center did a non bad undertaking inward creating it.

But, piece self-driving cars hope improved safety, precisely about critical issues must endure addressed to ensure they are at to the lowest degree every bit prophylactic every bit human-driven cars and, hopefully, fifty-fifty safer.

Machine learning is the surreptitious sauce for the recent success of self-driving cars as well as many other amazing figurer capabilities. With machine learning, the figurer isn’t programmed past times humans to follow a fixed recipe every bit it was inward traditional systems. Rather, the figurer inward number teaches itself how to distinguish objects such every bit a bush from a mortal most to cross a street past times learning from event pictures that label bushes as well as people.

Traditional software security evaluations banking concern check the software’s recipe against its actual behavior. But amongst machine learning, at that spot is no recipe — precisely a huge bunch of examples. So it is hard to endure certain how the automobile volition comport when it sees something that differs fifty-fifty slightly from an example.

To accept a uncomplicated example, maybe a automobile volition halt for pedestrians inward testing because it has learned that heads are round, but it has problem amongst odd chapeau shapes. There are then many combinations of potential situations that it is nearly impossible to only essay out the automobile until yous are certain it is safe.

Statistically speaking, fifty-fifty 100 i K m miles of driving is non plenty to exhibit that these cars are fifty-fifty every bit prophylactic every bit an average human driver. The Department of Transportation should address this key occupation caput on as well as require rigorous evidence that machine-learning results are sufficiently prophylactic as well as robust.

Influenza A virus subtype H5N1 key chemical ingredient of ensuring security inward machinery, except for cars, is independence betwixt the designers as well as the folks who ensure safety. In airplanes, trains, medical devices as well as fifty-fifty UL-listed appliances, ensuring security requires an independent exam of software design. This helps move on things prophylactic fifty-fifty when administration feels pull per unit of measurement area to transportation a production earlier it’s actually ready.

There are private-sector companies that ambit independent security certification for many dissimilar products, including cars. However, it seems that most automobile companies don’t purpose these services. Rather than only trust automobile companies to ambit the correct thing, the Department of Transportation should follow the atomic number 82 of other industries as well as require independent security assessments.

Wirelessly transmitted software updates tin strength out move on automobile software current. But volition your automobile even then endure prophylactic later a software patch? You’ve in all probability experienced yourself prison theater cellphone telephone or personal figurer updates that innovate novel problems.

The Department of Transportation’s proposed policy requires a security re-assessment alone when a “significant” alter is made to a vehicle’s software. What if a automobile society numbers a major novel software update 8.6.1 instead of 9.0 precisely to avoid a security audit? This is a huge loophole.

The policy should endure changed to require a security certification for every software alter that potentially affects safety. This sounds similar a lot of work, but designers guide maintain been dealing amongst this for decades past times partitioning vehicle software across multiple independent computers — which guarantees that an update to a non-critical figurer won’t bear upon unchanged critical computers. This is why non-critical updates don’t guide maintain to endure recertified.

Changing an icon on the radio computer’s display? No problem. Making a “minor” alter to the machine-learning information for the pedestrian sensor computer? Sorry, but nosotros desire an independent security banking concern check on that earlier crossing the street inward a wintertime hat.

Philip Koopman is an associate professor inward the Department of Electrical as well as Computer Engineering at Carnegie Mellon University. Michael Wagner is a senior commercialization specialist at CMU’s National Robotics Engineering Center. They are co-founders of Edge Case Research, which specializes inward autonomous vehicle security assurance as well as embedded software quality. The views expressed hither are personal as well as non necessarily those of CMU.

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Notes: It is of import to emphasize that the context for this slice is mainstream deployment of autonomous vehicles to the full general public. It is non intended to address limited deployment amongst trained security observer drivers. There are to a greater extent than issues that matter, but this word framed to check the target length as well as appeal to a broad audience.



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