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  • IMAGINE A WORLD WHERE YOU WAKE UP, GRAB YOUR CUP OF COFFEE, AND HOP IN YOUR CAR TO DRIVE

  • TO WORK

  • EXCEPT YOURE NOT DOING THE DRIVING.

  • YOU HAVE MORE TIME TO SLEEP, READ A BOOK, OR EVEN GET A PHYSICAL.

  • THIS IS A WORLD WE ALL WANT TO LIVE IN. AND ALTHOUGH WERE NOT QUITE THERE YET, PEOPLE

  • ALL OVER THE WORLD ARE WORKING ON DEVELOPING, TESTING, AND PLANNING FOR A

  • FUTURE WITH AUTONOMOUS VEHICLES.

  • BECAUSE, WHO DOESN’T WANT THAT EXTRA HOUR OF SLEEP?

  • SO, HOW CLOSE ARE WE TO A SELF-DRIVING WORLD?

  • YOU MAY HAVE SEEN SELF-DRIVING CARS ON THE NEWS, SPLASHED ACROSS THE INTERNET, OR EVEN

  • TESTING AROUND YOUR CITY.

  • BUT MOST OF THOSE CARS STILL HAVE A HUMAN IN THE DRIVER’S SEAT.

  • AND THAT MEANS IT’S PROBABLY A LEVEL 2 OR 3 CAR, WHICH DEFINITELY MORE INDEPENDENT THAN

  • THE CAR YOU MIGHT DRIVE, WHICH IS PROBABLY A LEVEL 0 OR 1, BUT IT'S STILL A FAR CRY FROM

  • OUR DREAM RIDE, WHICH WOULD BE A LEVEL 5.

  • OR 4.

  • LET ME EXPLAIN.

  • SAE INTERNATIONAL HAS DIVIDED AUTONOMY INTO FIVE STAGES.

  • LEVEL ONE ISDRIVER ASSISTANCE,” AND LEVEL TWO ISPARTIAL AUTOMATION,”

  • WHICH YOU CAN ALREADY FIND IN CARS WE DRIVE TODAY.

  • HERE, THE CAR CAN DO SOME OF THE STEERING, BRAKING, AND ACCELERATING, BUT STILL NEEDS

  • A DRIVER WITH HANDS ON THE WHEEL, BECAUSE LEVELS 1 AND 2 ARE STILL JUSTDRIVER SUPPORT.”

  • So lane keeping, collision warning, even active interventions that will swerve the vehicle

  • if you're about to get into an accident.

  • LEVEL THREE ISCONDITIONAL AUTOMATION,” WHICH MEANS THAT THE CAR IS PRETTY MUCH IN

  • CONTROL, BUT REQUIRES HUMAN INTERVENTION IN AN EMERGENCY,

  • OR WHEN PROMPTED BY THE SYSTEM.

  • REMEMBER LEVEL THREE, BECAUSE THIS IS WHERE IT CAN GET STICKY.

  • BUT THE ULTIMATE SELF-DRIVING CAR WOULD BE OPERATING AT LEVEL 4 OR 5, WHERE IT CAN STEER,

  • BRAKE, ACCELERATE, MONITOR THE ROAD, RESPOND TO RANDOM EVENTS, CHOOSE TO CHANGE LANES,

  • TURN, AND OF COURSE

  • USE ITS BLINKER LIKE ANY DECENT CITIZEN.

  • THE YELLOW BRICK ROAD TOWARD SELF-DRIVING TECHNOLOGY HAS BEEN A WINDING ONE.

  • DR. DEAN POMERLEAU HAS BEEN NAVIGATING IT FOR A LONG TIME.

  • YOU COULD CALL HIM THE GRANDFATHER, OR AT LEAST THE COOL UNCLE,

  • OF AUTONOMOUS VEHICLES.

  • BACK IN 1995, DEAN AND HIS GRADUATE STUDENT MADE A PILGRIMAGE ACROSS THE COUNTRY

  • "LOOK MA, NO HANDS”-STYLE, AFTER THEY TRICKED OUT A STYLISH MINIVAN WITH CAMERAS

  • AND COMPUTER VISION ALGORITHMS.

  • About 98.2% of the trip, as I recall, was hands-off, feet-off, with the system controlling

  • the vehicle all on its own.

  • It was a proof of concept, basically, for some of the technologies that we're seeing

  • finally being deployed today.

  • IN THE YEARS THAT FOLLOWED, RESEARCH TEAMS COMPETED

  • TO DEVELOP THAT TECHNOLOGY FURTHER.

  • IT WASN’T UNTIL 2005, AFTER SOME

  • CATASTROPHIC FAILURES, THAT DARPA’S GRAND CHALLENGE TO BUILD A SELF-DRIVING CAR FINALLY

  • AWARDED FIRST PLACE TO A STANFORD TEAM, LED BY SEBASTIAN THRUN.

  • YEAH, YOU MIGHTVE SEEN HIM AROUND.

  • FAST FORWARD TO 2009, WHEN HE STARTS A LITTLE PROJECT CALLED WAYMO.

  • IN SECRET.

  • IN 2016, WAYMO SPINS OFF FROM GOOGLE, AND IN A FEW SHORT YEARS, THE INDUSTRY’S ERUPTED,

  • WITH ESTABLISHED TECH AND CAR COMPANIES JUST AS EAGER AS STARTUPS TO GET IN ON THE ACTION.

  • Waymo is probably the recognized leader.

  • GM bought Cruise Automation; Argo AI here in Pittsburgh is one leading player;

  • BMW Mercedes, are all working on their own projects for self-driving cars.

  • It remains to be seen whether it's a good investment or not.

  • FOR THAT INVESTMENT TO PAY OFF, DRIVERLESS TECHNOLOGY MUST BE REFINED TO THE POINT

  • WHERE IT’S BOTH RELIABLE AND FLEXIBLE ENOUGH TO HANDLE A COMPLEX JOURNEY.

  • THAT MEANS SOPHISTICATED SENSORS, ROBUST COMPUTER HARDWARE,

  • AND INTELLIGENT DECISION-MAKING SOFTWARE.

  • TO START WITH, AUTONOMOUS VEHICLES RELY ON SOMETHING NOT ALL HUMAN DRIVERS

  • ARE EQUIPPED WITH: A SENSE OF DIRECTION.

  • The companies that are building these self-driving cars build their own maps.

  • Very much like Google has its street-view cars that drive through neighborhoods and

  • collect map data, they have another fleet with many additional sensors to drive through

  • a city and map it in great detailstatic obstacles, like telephone poles or the curbs

  • around the road, that it should be aware of and avoid.

  • BUT TO BE TRULY ADAPTIVE, THE CAR NEEDS TO BE ABLE TO GATHER REAL-TIME INFORMATION ABOUT

  • A DYNAMIC, UNPREDICTABLE ENVIRONMENT.

  • ELON MUSK THINKS WE CAN ACCOMPLISH THIS WITH CAMERAS ALONE.

  • BUT IF YOUVE EVER TAKEN A SELFIE IN THE CLUB, YOU KNOW THAT CAMERAS PROBABLY AREN’T

  • GOING TO CUT IT, BECAUSE THEY STILL STRUGGLE WITH DARKNESS, DEPTH, AND REFLECTIONS.

  • So self-driving-car companies are investigating many different sensors, for example, millimeter

  • wave radars for long-range sensing, and short-range, often ultrasound, sensors that see things

  • that are very close to the vehicle.

  • LiDAR is probably the most common and most impressive technology currently being used.

  • LiDAR is a laser-based technology that shoots a laser beam out into the environment, scans

  • it very quickly, and detects the range to objects and other vehicles.

  • LiDARs are both a great sensor but also a weak link; they're very expensive and

  • break down fairly often.

  • AND THIS HAS BEEN A MAJOR ROADBLOCK TO FULLY AUTONOMOUS ROADS.

  • LIDAR HAS HUGE POTENTIAL, BUT IT’S JUST TOO DELICATE AT THE MOMENT, BECAUSE IT’S

  • MADE UP OF FRAGILE, MOVING PARTS.

  • BUT SOMETHING CALLED SOLID-STATE LIDAR, WHICH SCANS THE ENVIRONMENT USING NO MOVING PARTS

  • COULD CHANGE ALL THAT.

  • AND THESE SENSORS, WHILE IN THEIR INFANCY, ARE IN SUCH DEMAND THAT MANUFACTURERS LITERALLY

  • CAN’T MAKE THEM FAST ENOUGH TO SUPPLY THE DEMANDS OF COMPANIES LIKE FORD AND BAIDU.

  • It's much more reliable and also much cheaper to manufacture, which is very important if

  • you're going to do this at scales on thousands of vehicles.

  • OKAY, SO SAY WE CAN BUILD A DRIVING ROBOT.

  • THAT IS, AN ENTITY THAT CAN PERCEIVE ITS ENVIRONMENT, JUDGE, AND ACT ON THE ROAD

  • BASED ON A COMPLEX NETWORK OF REAL-TIME DATA ANALYSIS.

  • IN A WAY, IT’S STILL ONLY PREPARED TO DRIVE ON A MAP.

  • TO BE ABLE TO NAVIGATE IN THE REAL WORLD, AND SHARE THE ROAD, AND THE STEERING WHEEL,

  • WITH HUMAN DRIVERS, WELL NEED TO TAKE IT TO DRIVER’S ED.

  • Some of the biggest safety concerns are involved with perception and behavior

  • of drivers or pedestrians or cyclists.

  • Slushy roads covered with ice and snow are very hard to cope with, and there's really

  • been very little effort or progress in self-driving cars in these very challenging environments.

  • TO MAKE THAT PROGRESS, WE HAVE TO STUDY HOW HUMAN DRIVERS ACTUALLY RESPONDBOTH TO

  • RISKY ROAD CONDITIONS, AND TO AUTONOMY ITSELF.

  • SO TO FIND OUT MORE ABOUT THE HUMAN IN THE WHOLE EQUATION, WE HEADED TO STANFORD’S

  • AUTOMOTIVE INNOVATION LAB.

  • We are working together to really get a detailed understanding of the human as we move forward

  • in designing active safety systems and automated vehicles.

  • So, we're gonna set up this NIRS cap on her right now.

  • It will be shining a little bit of infrared light onto her motor cortex.

  • We'll be able to see as she's turning left, turning right, using the gas pedal and the

  • brake pedal, all in our data streams back there.

  • The majority of accidents that we do see do come down to human error in either recognition,

  • decision, or performance.

  • So when we can get to the point where the system does a better job at those three things

  • than humans, then I think it's clear that our roads will be safer.

  • This is X-1, our experimental test vehicle.

  • The flexibility in steering allows us to set up all sorts of experiments.

  • We can emulate driving on an unexpected change of friction.

  • Going from snow to ice, for example.

  • There are studies going on in the dynamic design lab, measuring the inputs that professional

  • drivers make, so that we can try and understand what they're doing differently to drive right

  • at the limits of the vehicle. We can use that to inform the way that the autonomous vehicle

  • control algorithms are designed, so that hopefully, your autonomous vehicle will drive as well

  • as the very best human driver.

  • LENE’S MOST RECENT PROJECT INVESTIGATED A SCENARIO THAT MIGHT POP UP IN SOMETHING

  • LIKE LEVEL 3 AUTONOMY, WHERE THE CAR’S BEEN ROLLING SOLO WHEN SUDDENLY, IT ENCOUNTERS

  • SOME SCENARIO IT CAN’T MAKE SENSE OF, AND THE HUMAN DRIVER IS ASKED TO INTERVENE.

  • What our studies of brain and behavior tell us is that it's important to consider a period

  • of time when people's driving behavior may be significantly different if they've taken

  • control of a vehicle after a certain amount of time out of the loop.

  • We can see almost in real time the cognitive resources being deployed. They may have more

  • limited cognitive resources to deal with an emergency situation under those conditions.

  • It's potentially a quite dangerous situation if you're handing off control back and forth

  • with the system.

  • THOUGH IT MAY SEEM EXTREME FOR CONSUMERS TO MAKE THE JUMP FROM CRUISING AROUND

  • IN A LEVEL 1 CAR TO HOPPING IN A FULLY AUTONOMOUS ONE,

  • MANY RESEARCHERS AGREE THAT PARTIAL AUTONOMY

  • SHOULD ONLY BE RESERVED FOR TESTING PURPOSES.

  • AND UNFORTUNATELY, MOST OF THE ACCIDENTS THAT HAVE ALREADY OCCURRED HAVE

  • PROVEN THEM RIGHT.

  • I think the next five years or so of autonomous vehicle design is actually going to focus

  • more on the ways in which we can implement full autonomy in a much smaller, more controlled

  • environment, and sort of do it that way rather than necessarily going through this partial

  • autonomy stage to get there.

  • People are easily distractible, and that's the underlying problem that autonomous vehicles

  • are setting out to solve.

  • So NACTO cities believe that it needs to be really full automation to achieve the safety

  • benefits that are the major promise behind autonomous vehicles.

  • THE NATIONAL ASSOCIATION OF CITY TRANSPORTATION OFFICIALS

  • REPRESENTS 68 CITIES AND 11 TRANSIT

  • AGENCIES ACROSS NORTH AMERICA.

  • NACTO RECENTLY CONVENED TO DISCUSS HOW THE WORLD WILL PREPARE

  • FOR FULLY AUTONOMOUS CARS

  • TO BECOME A REALITY.

  • It's unrealistic to expect city governments to redesign streets

  • to accommodate autonomous vehicles.

  • THIS MEANS, WHEN SELF-DRIVING CARS DO HIT THE ROAD, THEYLL NEED TO TRAVEL AT LOW

  • SPEEDS, AND MAKE USE OF OUR EXISTING INFRASTRUCTURE.

  • BECAUSE OVER THE PAST CENTURY, WEVE MADE COUNTLESS COMPROMISES

  • TO ACCOMMODATE THE SHINY NEW TECHNOLOGY OF THE TIME

  • THE AUTOMOBILE.

  • BUT URBAN PLANNERS THINK WE CAN DO BETTER THIS TIME AROUND.

  • We've seen neighborhoods cut off from opportunities, we've seen congestion, greenhouse gas emissions,

  • pollution, decreases in public healthwe risk repeating a lot of those same mistakes

  • with autonomous vehicles.

  • The Bblueprint for Autonomous Urbanism came about because we were seeing too many visions

  • for driverless cars in a people-less city.

  • The Blueprint is imagining how cities can structure their streets to prioritize walking

  • and biking and transit and public space, to really maximize those benefits of living and

  • being in a city, while using autonomous vehicles to help achieve those goals.

  • THE IMAGES YOU SEE HERE ARE JUST SKETCHES AND SUGGESTIONS FOR THE FUTURE.

  • THE REALITY IS, REGULATION FOR THESE KINDS OF VEHICLES IS PRETTY NEWAND

  • IT’S DIFFERENT IN EVERY STATE.

  • BUT PLANNERS AND TRANSPORTATION OFFICIALS LARGELY AGREE ON THE NEED FOR EQUAL ACCESS,

  • SAFETY, AND SUSTAINABILITY.

  • It requires really thoughtful and intentional policies to make that vision and that promise

  • a reality.

  • SO, HUMANS ARE ADAPTABLE LEARNERS.

  • AND WERE DESIGNING SYSTEMS THAT CAN WORK THAT WAY TOO.

  • BUT ON A GRANDER SCALE, WE AS A SOCIETY HAVE TO BE WILLING TO ASSESS RISK, AND STEER IN

  • THE RIGHT DIRECTION BEFORE WE CHANGE LANES AND CHARGE FULL SPEED AHEAD.

  • SO

  • HOW CLOSE ARE WE TO A DRIVERLESS WORLD?

  • If you look at particular geographical locations, it's already happening.

  • Over time, I believe that those islands will grow in number and expand, and that's how

  • you will see the expansion of fully automated vehicles on the road.

  • I think in the next year or two we will see companies like Waymo and GM Cruise deploying

  • maybe a few hundred of these vehicles for the general public to ride in.

  • Probably by early 2020s, we'll see cars without drivers giving rides and then driving empty

  • to pick up the next passenger.

  • It'll be probably at least a decade, I would say, before you can walk into a showroom and

  • buy a car at an affordable price that can do, say, level four or five autonomy, which

  • means you don't have to do anything.

  • The fact that Waymo's CEO said we're still quite a ways off makes me think

  • that that's probably true.

  • But in the near term, I think there are some applications, especially for transit, to use

  • autonomous technology to achieve some of our goals.

  • Access to affordable, convenient transportation is really important.

  • We all have a grandparent or a friend of our grandparents who had to give up driving and

  • lost a lot of their independence.

  • I think it can change lives and save lives across the board as long as we take into consideration

  • everyone across the spectrum as we as a society move forward with automated vehicles.

  • SOUNDS LIKE AS LONG AS WE TAKE CARE OF SOME POTHOLES FIRST

  • WEVE GOT A GREEN LIGHT.

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  • THANKS FOR WATCHING AND I'LL SEE YOU NEXT TIME ON SEEKER.

IMAGINE A WORLD WHERE YOU WAKE UP, GRAB YOUR CUP OF COFFEE, AND HOP IN YOUR CAR TO DRIVE

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