Speaker 1: Get in touch with technology with tech Stuff from how
Speaker 1: stuff Works dot com. Hey there, and welcome to tech Stuff.
Speaker 1: I'm your host, Jonathan Strickland. I'm an executive producer with
Speaker 1: how Stuff Works in I heart radio and I love
Speaker 1: all things tech. And in our last episode, if you
Speaker 1: haven't heard that, you should probably go and listen to it.
Speaker 1: But I left off with Ernest Dickmans, the German engineer
Speaker 1: who had done amazing work with dynamic computer vision and
Speaker 1: vehicle automation in the nineteen eighties and nineties. But that
Speaker 1: work would only go as far as the sophistication of
Speaker 1: the technology of the time would allow, and funding for
Speaker 1: AI work had gotten pretty darn scarce in the eighties
Speaker 1: and nineties. So while he and his team were prepping
Speaker 1: for their ninety four demonstrations that were so impressive, there
Speaker 1: was similar work going on in the United States. From
Speaker 1: to nine. Research teams took advantage of six hundred fifty
Speaker 1: million dollars of funding created by the US government through
Speaker 1: the Intermodal Surface Transportation Efficiency Act. That act was meant
Speaker 1: to support planning for several transportation projects, uh including the
Speaker 1: creation of new rail lines between various cities. At the
Speaker 1: autonomous research was really just one piece of this larger legislation.
Speaker 1: And also just to let you guys know, in case
Speaker 1: you're curious, many of those projects did not receive enough
Speaker 1: funding to really accomplish their goals, so they never really
Speaker 1: self fruition. It's one of the downsides of government projects
Speaker 1: is that the budgets are too low. Nothing of real
Speaker 1: import tends to happen. People might get paid by some
Speaker 1: of that money, but the actual projects don't necessarily, you know, happen.
Speaker 1: On the driver list car side, nine organizations began to
Speaker 1: work on technologies to make driverless cars a reality, but
Speaker 1: the deadline for meeting those goals in a suitable demonstration
Speaker 1: was and from what I can tell, not a whole
Speaker 1: lot of progress was made in that time, or at
Speaker 1: least not enough to end up with an impressive demonstration.
Speaker 1: That marked a point in history that we would say,
Speaker 1: this is really important in driver lest cars. But we're
Speaker 1: continued on the various systems that would be necessary to
Speaker 1: make driverless cars. But you would argue that driverless car
Speaker 1: research and development as a whole, as a as a
Speaker 1: goal in of itself, was kind of shelved for a while.
Speaker 1: There were people working on various parts of the problem.
Speaker 1: Most of them were working in fields that ultimately would
Speaker 1: prove important to the development of driverless cars. But again,
Speaker 1: they were doing this for other reasons, and it wasn't
Speaker 1: necessarily as uh an in goal of creating an autonomous vehicle.
Speaker 1: Much of the excitement and money around the concept had
Speaker 1: died down by the mid to late nineties. Some of
Speaker 1: those related research projects would end up growing out of
Speaker 1: a US backed R and D project called the Strategic
Speaker 1: Computing Initiative or s c I now that actually got
Speaker 1: started in ninety three. The goal of the initiative was
Speaker 1: incredibly ambitious. That's a very kind way of putting it.
Speaker 1: I'd actually say it was unrealistically ambitious. It was to
Speaker 1: develop the technology to create a machine learning system capable
Speaker 1: of running quote, ten billion instructions per second to see here,
Speaker 1: speak and think like a human. The degree of integration
Speaker 1: required would rival that achieved by the human brain, the
Speaker 1: most complex instrument known to man. End quote. That was
Speaker 1: actually written in an account by Alex Rowland and Philip
Speaker 1: Shiman for the m I T Press about the s
Speaker 1: c I project. The goal was to achieve that in
Speaker 1: just a deck aid so starting in nineteen eighty three,
Speaker 1: the plan was that by ninetee, we're gonna have a
Speaker 1: computer that can think and and experience like a human can. Wowsers.
Speaker 1: So it's pretty obvious by the late eighties that this
Speaker 1: was not gonna happen. They were not going to hit
Speaker 1: that goal, and in retrospect, we would probably call this
Speaker 1: the result of hubrists. The human brain is far more
Speaker 1: complicated and technology is far more limited than we gave
Speaker 1: either credit for back in nineteen eighty three. Nevertheless, the
Speaker 1: Defense Advanced Research Projects Agency or DARPA and the Department
Speaker 1: of Defense, which is the department that oversees DARPA, poured
Speaker 1: about a billion dollars into funding various programs throughout the
Speaker 1: United States in an effort to achieve this goal. And
Speaker 1: while we did not get a computer that thinks like
Speaker 1: a person out of this whole process, many influential computer
Speaker 1: scientists and research projects were able to advance our capabilities
Speaker 1: and understanding through their work which got funding from this project.
Speaker 1: So we didn't get what the project was aimed to produce,
Speaker 1: but we did benefit from it. Some of that work
Speaker 1: would become really important for the next big DARPA initiative
Speaker 1: that I'm going to cover, and that is the Grand Challenge.
Speaker 1: The history of the Grand Challenge dates back to two
Speaker 1: thousand one. At that time, the United States Congress had
Speaker 1: its own challenge for the various branches of the U. S. Military.
Speaker 1: The US Congress said, we want you to develop the
Speaker 1: technology necessary to allow one third of all military ground
Speaker 1: combat vehicles to be unscrewed by two thousand fifteen. In
Speaker 1: other words, to have autonomous ground combat vehicles one third
Speaker 1: of all of them. The purpose, obviously was to keep
Speaker 1: soldiers out of harm's way as much as possible. That
Speaker 1: if you could have these ground combat vehicles operate autonomously,
Speaker 1: then if one gets destroyed, that's a huge amount of
Speaker 1: money gone down the drain, but no one dies, at
Speaker 1: least no one on your side dies. Achieving this goal
Speaker 1: would also be super difficult to do. Technology just wasn't
Speaker 1: where it would need to be by itself. The defense
Speaker 1: contractors that DARPA would work with on these sort of
Speaker 1: solutions weren't making the progress necessary in order to meet
Speaker 1: that two thousand fifteen goal, and DARPA recognized this early on.
Speaker 1: They said, this is just not gonna happen. So in
Speaker 1: the final report for the two thousand four Grand Challenge,
Speaker 1: which was the first of the three Grand Challenges around
Speaker 1: autonomous cars, the logic that the agency laid out to
Speaker 1: justify this challenge was this, while there have been a
Speaker 1: number of significant technical breakthroughs leading to robust unmanned air
Speaker 1: vehicles that US forces used today, progress in unmanned autonomous
Speaker 1: ground vehicle technology has not occurred at a similar rate.
Speaker 1: Vehicle operations in a ground environment are a much more
Speaker 1: difficult challenge due to terrain, man made obstacles, and weather
Speaker 1: that's just scratching the surface. They actually were pretty you know,
Speaker 1: generous in that regard, because as it turns out, there
Speaker 1: are a lot of other factors that make this a
Speaker 1: really difficult problem. And I think one other thing quick
Speaker 1: tangent that I think is important here is DARPA pointing out, yes,
Speaker 1: we came up with autonomous systems for aircraft ages ago.
Speaker 1: We have lots of them. We have unmanned drones that
Speaker 1: we can fly, but we haven't really done that with cars.
Speaker 1: I think that's also a good reminder that technology does
Speaker 1: not all progress at the same accelerated rate. We have
Speaker 1: more is law, which has kind of conditioned us to
Speaker 1: think about our technology advancing rapidly over the course of
Speaker 1: every two years. But that doesn't apply to every technology.
Speaker 1: It applies specifically these days to computational power, and originally
Speaker 1: only dealt with the number of transistors you could fit
Speaker 1: on a square inch of silicon wafer. So this is
Speaker 1: good to remember because I think a lot of futurists
Speaker 1: just kind of apply More's law to all technologies and
Speaker 1: just assume that everything is accelerated at that saint or
Speaker 1: everything is moving at that same accelerated rate. Back to
Speaker 1: autonomous cars. Jose Negron, who worked at DARPA at the
Speaker 1: time of the Grand Challenges, went to the director of
Speaker 1: DARPA with an idea, and he said, there are a
Speaker 1: lot of people out there who could potentially contribute to
Speaker 1: the advancement of technology we're going to need for autonomous cars.
Speaker 1: But we normally would work with them because they're independent innovators,
Speaker 1: They work with smaller groups, they aren't part of defense
Speaker 1: contractor companies, and so they don't often get a chance
Speaker 1: to do any sort of work for the Department of Defense.
Speaker 1: But we could take advantage of them if we are
Speaker 1: if we give them the chance to participate, we could
Speaker 1: benefit from that and they might create the breakthroughs that
Speaker 1: we need to meet that two thousand fifteen deadline. And so,
Speaker 1: after a couple of years of funding various research projects,
Speaker 1: the then director of DARPA was a guy named Tony Teather.
Speaker 1: Anthony Tather announced a new initiative and it was for
Speaker 1: an open challenge to any teams that wanted to participate.
Speaker 1: Anyone could apply to be part of this challenge. Specifically,
Speaker 1: the challenge was to develop autonomous vehicle technology and incorporate
Speaker 1: it into a vehicle that could traverse a one forty
Speaker 1: two mile course without human intervention. So from the start
Speaker 1: of the course to the end of it, the vehicle
Speaker 1: would have to be operating under its own abilities, its
Speaker 1: own power. The team to complete this course in the
Speaker 1: shortest amount of time would take home a million dollars. Now, initially,
Speaker 1: Anthony Tather was skeptical that this announcement was going to
Speaker 1: draw much interest. He said, we'll get a shot, but
Speaker 1: I don't think very many people are going to respond.
Speaker 1: DARPA scheduled a kickoff event at the Peterson Automotive Museum
Speaker 1: in Los Angeles, California for anyone interested in participating. On
Speaker 1: the day of that event, Anthony Tather arrived at the
Speaker 1: venue a half hour before the scheduled time to start,
Speaker 1: and he discovered there was a line wrapping around the
Speaker 1: block of people who were interested in participating. According to
Speaker 1: the final report for the two thousand four Challenge, more
Speaker 1: than four hundred people showed up to that first conference.
Speaker 1: The race course for this two thousand four event would
Speaker 1: end up being incredibly challenging. A guy named Salve Fish
Speaker 1: actually designed the course and he made it really tough.
Speaker 1: Vehicles would travel through the desert, including trips up and
Speaker 1: down hills and through switchbacks. Sometimes the road would narrow
Speaker 1: down to about ten feet wide. There are points where
Speaker 1: the road would drop off several feet to one side
Speaker 1: or the other. The course crossed railroad tracks. There was
Speaker 1: the chance that the cars might encounter animals along the course.
Speaker 1: DARPA had some professional drivers actually go down this course
Speaker 1: after it had been established to kind of give their
Speaker 1: estimation of it, and they said it was fairly challenging
Speaker 1: even for a professional trained off road driver. Any autonomous
Speaker 1: car that was to complete this course was expected to
Speaker 1: do so within ten hours of starting, so there's a
Speaker 1: ten hour time limit essentially from start to finish. So
Speaker 1: why did they make it so challenging. Well, keep in mind,
Speaker 1: the ultimate goal of this and the following challenges was
Speaker 1: to encourage the development of technology that would allow the
Speaker 1: US military to build autonomous military vehicles. And the US
Speaker 1: was and still is, heavily involved in operations in the
Speaker 1: Middle East, and so the course was partly designed to
Speaker 1: mimic the conditions that military vehicles might regularly encounter in
Speaker 1: that part of the world. And while on a test
Speaker 1: we might say, while that's really challenging, in a real
Speaker 1: world scenario, we don't really. We can't change the parameters.
Speaker 1: It's it is what it is. So it needed to
Speaker 1: be really hard. It needed to be hard also to
Speaker 1: spur on that innovation. The course would begin in Barstow, California,
Speaker 1: and it would end in prem Nevada, passing through the
Speaker 1: Mojave Desert. All right, I'm gonna talk about how this
Speaker 1: challenge unfolded, but first let's take a quick break to
Speaker 1: thank our sponsor. The teams had just one year to develop, build, test,
Speaker 1: and complete their technologies. So, like I said, this was
Speaker 1: an enormous challenge. Competing teams included universities, there were research facilities,
Speaker 1: There are some company teams. There were even some high
Speaker 1: school teams that applied. DARPA received one hundred six applications. Now,
Speaker 1: not everyone who attended the kickoff event went through with
Speaker 1: the step of applying, and the rules did restrict who
Speaker 1: could participate. They said US federal government organizations could not
Speaker 1: participate in this event. Federal employees could participate, but only
Speaker 1: as a private citizen on a team. They could not
Speaker 1: represent a federally backed team. Federal funding wasn't allowed either,
Speaker 1: and teams were prohibited from using government owned equipment, with
Speaker 1: one exception, which was that if the government were to
Speaker 1: offer equipment to all teams, that's fine, but no team
Speaker 1: could just take advantage of government owned equipment if they
Speaker 1: were the only team that had access to it. DARPA
Speaker 1: set up a website for the competition that included a
Speaker 1: forum and which interested parties could post questions. They could
Speaker 1: share advice, They could share strategies for how they were
Speaker 1: going to solve really hard problems like obstacle detection, path finding,
Speaker 1: position location, the control software that would be needed for
Speaker 1: the vehicle itself. Teams could also help each other find sponsors,
Speaker 1: to help get money and funding to cover expenses, and
Speaker 1: it sounds to me like it was a fairly collaborative
Speaker 1: space despite the competitive nature of the objective. The general
Speaker 1: strategy for most teams was to pair several technologies together
Speaker 1: to create an autonomous car, so they weren't necessarily developing
Speaker 1: all these tools themselves. In some cases, they were making
Speaker 1: use of existing tools, so a lot of them would
Speaker 1: use stuff like a GPS receiver. I've talked about GPS
Speaker 1: extensively not too long ago, so I'm not going to
Speaker 1: go over that again. Also optical sensors, so essentially cameras
Speaker 1: and similar sensors, laser range finders, lidar systems, things like that.
Speaker 1: Some teams spent most of their time developing the computer
Speaker 1: programs that would make decisions based on the incoming data
Speaker 1: from these various sensors, such as whether a vehicle should
Speaker 1: accelerate to climb a steep hill or to break to
Speaker 1: avoid going off the edge of the road, or to
Speaker 1: steer in a particular direction. One team created a system
Speaker 1: that used a voting mechanism to decide on what to
Speaker 1: do at any given point, and it would wait various
Speaker 1: factors in that decision making process so that the computer
Speaker 1: could arrive at what it thought was the best course
Speaker 1: of action for any given set of circumstances. DARPA chose
Speaker 1: twenty five of the teams after reviewing their technical applications,
Speaker 1: and immediately upon looking at the technical applications, they were
Speaker 1: able to select nineteen teams by itself, They said, all right,
Speaker 1: these nineteen really have a solid application. For the other six.
Speaker 1: They visited several of those teams for site visits, kind
Speaker 1: of to get an idea of how far along each
Speaker 1: project was, how realistic the chances were that the team
Speaker 1: was going to be ready by race time, and generally
Speaker 1: just get a gut feeling for who had a real
Speaker 1: chance to to do something special at this competition. The
Speaker 1: teams were invited to a qualifying event at the California
Speaker 1: Speedway in Fontana, California, and of the twenty five that
Speaker 1: were selected, twenty one showed up. Four teams did not
Speaker 1: make it to the qualifying event. The qualifying event tested
Speaker 1: vehicles in many ways, including responsiveness, speed, safety. They went
Speaker 1: through some areas that would simulate what the cars would
Speaker 1: encounter on the actual race. Only seven teams were actually
Speaker 1: able to navig Gate the full qualifier, but DARPA selected
Speaker 1: another eight on top of the seven that made it through.
Speaker 1: They were close enough for consideration, and so the on
Speaker 1: plus teams that had applied the competition was narrowed down
Speaker 1: to fifteen teams. For the big race itself, DARPA had
Speaker 1: some other special rules. One was that each team would
Speaker 1: not be given any information about the course until about
Speaker 1: two hours before the actual start time. Another was that
Speaker 1: a human driven chase vehicle would follow each of the
Speaker 1: autonomous vehicles, and inside that chase vehicle there would be
Speaker 1: a laptop operated by a team member that would allow
Speaker 1: them to activate a kill switch. So if an autonomous
Speaker 1: car or motorcycle more on that in a second where
Speaker 1: to go nuts, start careening off course and driving out
Speaker 1: of control, a human in the chase vehicle could hit
Speaker 1: the kill switch and that would shut down the target
Speaker 1: vehicle before any real calamity could occur. The cars weren't
Speaker 1: meant all to leave at the same time. It wasn't
Speaker 1: like that kind of race where they all lined up
Speaker 1: and then the flag dropped. There was a staggered departure
Speaker 1: time UH, and it was staggered by several minutes so
Speaker 1: the goal was to have the fastest time from start
Speaker 1: to finish, but not necessarily to physically race against another
Speaker 1: vehicle in real time, although there was the potential that
Speaker 1: a car could catch up with whichever vehicles were in
Speaker 1: front of it and pass it that way, that was
Speaker 1: a possibility. DARPA told CNN that about five people were
Speaker 1: working on the race in total, some of them were volunteers,
Speaker 1: some of them were DARPEST staff members, and that the
Speaker 1: race also employed several wreckers tow trucks. Essentially, so if
Speaker 1: vehicles got stuck, a wrecker could come in and pull
Speaker 1: them out of the way, and that vehicle would obviously
Speaker 1: be uh. It would be eliminated from the race. Uh
Speaker 1: and whoever pass that finished line in the shortest amount
Speaker 1: of time would walk away with a cool one million
Speaker 1: dollars in prize money. Now, one of the participants in
Speaker 1: this race, just as a moment of interest here was
Speaker 1: a guy named Anthony Lewandowski. And I've talked about Lewandowski
Speaker 1: in tech stuff. I think it was a year ago
Speaker 1: when I was talking about Lewandowski. His approach was unique
Speaker 1: in that he brought a self balancing motorcycle to the
Speaker 1: event rather than a four wheeled vehicle. Lewandowski became somewhat
Speaker 1: infamous for departing Google he worked in their autonomous vehicle
Speaker 1: department and then going to work for Uber and then
Speaker 1: allegedly bringing along with him some proprietary information from Google.
Speaker 1: So that was what I was talking about the last
Speaker 1: time I chatted about Lewandowski. The fifteen teams, in order
Speaker 1: of their start time were the Red Team from Carnegie
Speaker 1: Mellon University, PSI Autonics two from Thousand Oaks, California, Team
Speaker 1: cal Tech from California Technical University, Digital Auto Drive or
Speaker 1: Dad from Morgan Hill, California, Virginia Tech which is from Virginia,
Speaker 1: Axion Racing from Westlake Village, California, Team Cajun Bot which
Speaker 1: might have my favorite name there from Lafayette, Louisiana, Team
Speaker 1: Endsco from Falls Church, Virginia, Team SIMAR that's see I
Speaker 1: M A R from Gainesville, Florida, and Logan, Utah. It
Speaker 1: was a joint project the Palos Verdes High School Road
Speaker 1: Warriors from Palace Very Days Estates, California, PSI A Tonics
Speaker 1: one from Thousand Oaks, so they actually left the starting
Speaker 1: line well after PSI A Tonics too uh. Team Tera
Speaker 1: Max from Oshkosh, Wisconsin, Team Tara Hawk from Guardina, California,
Speaker 1: the Golem Group from Santa Monica, California, and the Blue
Speaker 1: Team from Berkeley, California. At six thirty in the morning
Speaker 1: on Saturday, March two thousand four, the Red Team's vehicle
Speaker 1: called Sandstorm so It's a Sandstorm from Carnegie Mellon became
Speaker 1: the first of the driver lest cars to tackle this course. Now,
Speaker 1: it would get about seven and a half miles down
Speaker 1: the road, but then it got stuck while trying to
Speaker 1: navigate a tight switchback. It was the most successful of
Speaker 1: all the vehicles, seven and a half miles out of
Speaker 1: a forty two So out of the fifteen cars that
Speaker 1: made it through to the competition, two of them withdrew
Speaker 1: prior to the start of the race. That would be
Speaker 1: Tara Hawk and Blue Team. Four of them didn't make
Speaker 1: it out of the starting area because of various problems
Speaker 1: ranging from steering abnormalities to colliding with wall, which I
Speaker 1: guess in its way as its own steering abnormality. Then
Speaker 1: you had Team Ends Goes vehicle which made it point
Speaker 1: two miles before it flipped over. Team Simar's car got
Speaker 1: tangled up by wire. Half a mile in the Golden
Speaker 1: Group's vehicle got stuck on an incline and couldn't provide
Speaker 1: enough throttle to overcome it. Team Terra Max's vehicle kept
Speaker 1: detecting bushes and eventually just stopped moving forward after it
Speaker 1: thought that there were bushes everywhere. I guess wouldn't budge.
Speaker 1: Team cal Tex car went off course and through a
Speaker 1: fence and could not get back on course, and so
Speaker 1: it was disqualified. So none of the vehicles were able
Speaker 1: to complete this on two mile course, not by a
Speaker 1: long shot. No one collected the million dollars. But DARPA
Speaker 1: wasn't about to give up there. For one thing, the
Speaker 1: agency had created an incredibly ambitious challenge, a really hard one,
Speaker 1: and for another, the teams were learning from their mistakes,
Speaker 1: and so DARPA chose to announce a second challenge that
Speaker 1: would take place in two thousand five. It would double
Speaker 1: the prize money to two million dollars and the ameters
Speaker 1: of the challenge would change slightly. Now, according to the
Speaker 1: final report for the two thousand four challenge, the agency
Speaker 1: quote believes it prudent to continue with the prize authority
Speaker 1: approach and hold a second Grand Challenge for autonomous unmanned
Speaker 1: ground vehicles in two thousand five. The prize authority approach
Speaker 1: is meeting the goals of attracting new talent with new
Speaker 1: ideas and accelerating advancement in robotic vehicle research. Without the
Speaker 1: Grand Challenge, it is doubtful there would be much progress
Speaker 1: without substantial new investment in accelerating research on autonomous ground
Speaker 1: vehicles that could traverse difficult terrain at militarily relevant speeds
Speaker 1: end quote. So how did that turn out? Well, I'll
Speaker 1: tell you. First thing, get a drink of water, and
Speaker 1: we're gonna thanks O our sponsors here. As Anthony Tether
Speaker 1: would say later, the thing to remember was the two
Speaker 1: thous and four Grand Challenge was something new. It had
Speaker 1: never been done before, and it was an engineering challenge
Speaker 1: open to anyone, and teams that were able to meet
Speaker 1: the selection criteria were able to participate. So while there
Speaker 1: was disappointment when no car was able to make it
Speaker 1: over the big hill that Sandstorm got stuck on, it
Speaker 1: didn't diminish the excitement for a second Grand Challenge. Returning
Speaker 1: teams were energized by the need to outperform their previous
Speaker 1: attempts and new teams came forward inspired by the original challenge.
Speaker 1: So while it could have been the needle that would
Speaker 1: deflate the autonomous balloon could lead to another artificial intelligence winter.
Speaker 1: Like I said in the last episode, it actually got
Speaker 1: more people excited about those possibilities. So in August two
Speaker 1: thousand four, DARPA held another participants conference for parties that
Speaker 1: were interested in either participating or sponsoring a team. Now,
Speaker 1: remember it just held the Grand Challenge in March. Now
Speaker 1: it's August and they're ready to talk about the next one.
Speaker 1: The new challenge was scheduled for October eight, two thousand five,
Speaker 1: and the rules allowed for flexible starting time, So if
Speaker 1: the weather was bad or other conditions were such that
Speaker 1: you couldn't really start in October eight, you would start
Speaker 1: the next day or the next up to October eighth,
Speaker 1: two thousand five. If it kept missing it up to
Speaker 1: that point, the whole thing would be canceled. Now, according
Speaker 1: to the rules, they said the route would be quote
Speaker 1: no longer than one miles end quote. I guess that
Speaker 1: was a relief since no one got past seven and
Speaker 1: a half miles in the first one, and also said
Speaker 1: the route would include quote paved roads, unpaved roads, trails,
Speaker 1: and off road desert areas. Examples of obstacles include ditches, berms, washboard,
Speaker 1: sandy ground, standing water, rocks and boulders, narrow underpasses, construction equipment,
Speaker 1: concrete safety rails, power line towers, barbed wire fences, and
Speaker 1: cattle guards end quote. The rules also stated that DARPA
Speaker 1: could introduce obstacles onto the course. They could purposefully put
Speaker 1: some obstacles in the way, but that the route would
Speaker 1: be wide enough so that a vehicle could bypass the
Speaker 1: obstacles without going off course. So they weren't going to
Speaker 1: block a road entirely, but they would at least partially
Speaker 1: block the road in certain locations. Now, if you want
Speaker 1: proof that the two thousand four challenge did not discourage
Speaker 1: IT participants, you just have to look at how many
Speaker 1: people and teams applied to be part of the two
Speaker 1: thousand five challenge. There were a hundred six people or
Speaker 1: teams that applied in two thousand four and two thousand
Speaker 1: five it was one hundred nine five teams, nearly twice
Speaker 1: as many that showed interest the year before. Out of
Speaker 1: those on DARPAT selected one eighteen teams for site visits.
Speaker 1: Out of those on eighteen, they chose forty that were
Speaker 1: selected to go on to the national qualification event, and
Speaker 1: then they picked three more alternate teams that were added
Speaker 1: in August two thousand five. Now, like the two thousand
Speaker 1: four qualifying event, this one was designed to sim relates
Speaker 1: some of the conditions for the final race, with the
Speaker 1: goal of reducing the number of competitors to the top
Speaker 1: twenty teams. All but one of the teams passed the
Speaker 1: initial technical inspections to make certain the vehicles met all
Speaker 1: the safety and performance parameters, and according to a news
Speaker 1: release from October two thousand five, twenty two robotic vehicles
Speaker 1: were able to get through the obstacle course designed to
Speaker 1: simulate the final race. DARPA actually would select twenty three
Speaker 1: teams to compete on the day of the race. They
Speaker 1: included returning teams like Cajun Butt, cal Tech, and Team Dad,
Speaker 1: and there were new teams to like Team Cornell, Desert
Speaker 1: Buck Eyes, the Gray Team, Insight Racing, and Stanford Racing Team.
Speaker 1: The final course for the two thousand five Challenge was
Speaker 1: one thirty one point two miles, which is about two
Speaker 1: hundred eleven kilometers. Out of the twenty three competing teams,
Speaker 1: five teams finished the full course. Only four of them
Speaker 1: did so within the ten hour time limit. The Terra Max,
Speaker 1: which was fifth place, would finish in twelve hours fifty
Speaker 1: one minutes, so it took a little too long to
Speaker 1: make that ten hour time limit, but it's still finished.
Speaker 1: All the other vehicles experienced either mechanical or software failures
Speaker 1: somewhere along the route and we're unable to complete the
Speaker 1: full course. The winning team of the two thousand five
Speaker 1: challenge was the Stanford Racing Team and their vehicle named Stanley.
Speaker 1: The average speed for Stanley was nineteen point one miles
Speaker 1: per hour, which is about thirty one kilometers per hour.
Speaker 1: Stanley was built on top of a Volkswagen tou Egg,
Speaker 1: which could be largely operated by an onboard computer by
Speaker 1: linking it to the vehicle's electrical system. However, they did
Speaker 1: still have electro mechanical parts to operate the steering and
Speaker 1: the gearshift, so it wasn't all done purely electronically yet.
Speaker 1: Stanley had five lie Dar units that could gather data
Speaker 1: for the vehicle's computer to build out a three dimensional
Speaker 1: map of its surroundings and pair that with GPS information,
Speaker 1: and there was some other positional equipment aboard Stanley as
Speaker 1: well to help supplement the information gathered by the GPS receiver.
Speaker 1: The computer system operated on Lenox, so Lenox fans out there,
Speaker 1: that was the computer system that was running on Stanley.
Speaker 1: According to Stanford, the code for the vehicle's behavior consisted
Speaker 1: of a hundred thousand lines, and it's decision making process
Speaker 1: was guided by machine learning. The team completed the course
Speaker 1: in six hours fifty four minutes, and that meant that
Speaker 1: they came in about eleven minutes ahead of second place.
Speaker 1: Second place went to Red Team's Sandstorm vehicle. Again, that's
Speaker 1: Carnegie Mellon University, and they were the one who once
Speaker 1: who got the furthest the year before. But Red Team
Speaker 1: had also fielded another card. They didn't just put in one,
Speaker 1: they put in two, and the one was called Highlander
Speaker 1: with a one in place of the eye. I guess
Speaker 1: there can be only one, but anyway, they put forward
Speaker 1: Highlander as well. That one came in third place, so
Speaker 1: Carnegie Melon took second and third place. It was nine
Speaker 1: minutes slower than Sandstorm, so it was about twenty minutes
Speaker 1: behind the first place winner. Now interesting side note about Highlander.
Speaker 1: Initially it was making great time, like really really good time.
Speaker 1: It was on track to win the whole darn thing.
Speaker 1: But about two hours after starting the race, the vehicle's
Speaker 1: engine began to sputter a bit, and it struggled anytime
Speaker 1: it hit a steep climb, and it was never able
Speaker 1: to get up to full speed even on a flat
Speaker 1: or or declined surface. So the Carnegie Melon team was
Speaker 1: really curious. They were wondering what the heck was going wrong,
Speaker 1: and they tried to figure out what happened at the
Speaker 1: end of the race. They weren't really able to nail
Speaker 1: it down at that point. They checked the fuel. The
Speaker 1: fuel was fine. It wasn't contaminated or old or anything
Speaker 1: like that. The oil was fine. The engine appeared to
Speaker 1: work just fine from a cold start, and it wouldn't
Speaker 1: be more. It would take more than a decade before
Speaker 1: they figured out what had gone wrong, and it was
Speaker 1: just by luck that they figured it out. Now, this
Speaker 1: is going to include a spoiler, but it's a spoiler
Speaker 1: for something that happened in two thousand seven, So I
Speaker 1: don't think it's really that big a deal. In Carnegie
Speaker 1: Mellon University was celebrating the tenth anniversary of the team's
Speaker 1: DARPA Urban Challenge win from two thousand seven, and I'll
Speaker 1: be talking about the DARPA Urban Challenge in our next
Speaker 1: episode well. As part of this celebration, they brought out
Speaker 1: Sandstorm and Highlander from storage. The two vehicles had been
Speaker 1: stored away, but they still existed while they were doing it.
Speaker 1: Spencer Spiker, who was part of the team working on this,
Speaker 1: was running some diagnostics on the Highlander engine it was
Speaker 1: running at the time, and as it was going through
Speaker 1: this process, he was leaning against the vehicle and the
Speaker 1: engine began to sputter, and when he moved away, the
Speaker 1: engine started to pick up again, and he realized that
Speaker 1: there was a little box that if there was pressure
Speaker 1: put on that little box, it started to cause the
Speaker 1: engine to die. That little box turned out to be
Speaker 1: a filter that sat between the car's engine control module
Speaker 1: and the fuel injectors, and he found out that if
Speaker 1: there were any pressure put on that filter, it was
Speaker 1: causing the engine to lose power. And leading up to
Speaker 1: the Grand Challenge, there was an incident that may have
Speaker 1: caused this problem. The Highlander had been going through a
Speaker 1: uh kind of a routine training exercise, and as it
Speaker 1: was doing so, it got too far over to one
Speaker 1: edge of a sloped path and it slid off that
Speaker 1: sloped path and it actually flipped over. Now, apparently that accident,
Speaker 1: which appeared to be minor, it didn't seem like it
Speaker 1: had caused that much damage, had actually bent this little box,
Speaker 1: this filter in such a way that because of its
Speaker 1: contact with the engine, was causing failure under the right conditions,
Speaker 1: such as when pressure was put on it or when
Speaker 1: it would expand from engine heat. And so the Highlander,
Speaker 1: after it would start to heat up, would start to
Speaker 1: lose performance, and it lost time during the Grand Challenge,
Speaker 1: about forty minutes worth of time according to most estimates,
Speaker 1: which would have made all the difference. It would have
Speaker 1: come in first place by twenty minutes if that had
Speaker 1: not happened. So it may have won if it hadn't
Speaker 1: been for that accident that had happened earlier. Making things
Speaker 1: even more juicy is that the leader of the Standard
Speaker 1: team that did win was Sebastian Throne, who had previously
Speaker 1: served as a member of the faculty at Carnegie Mellon University.
Speaker 1: He was In fact, a colleague of the head of
Speaker 1: CMUs team read Whittaker, So the Red team's Red Whittaker,
Speaker 1: the Carnegie Mellon University team leader used to work with
Speaker 1: the guy who led the Stanford team, So there was
Speaker 1: some rivalry going on there, although from what I've read,
Speaker 1: it sounds like it was all very good natured rivalry.
Speaker 1: It wasn't like it was super bitter or anything. Now,
Speaker 1: the nice thing is no one seems particularly mad that
Speaker 1: this happened. It's the sort of thing that can happen
Speaker 1: with mechanical systems in general. And ultimately, Carnegie Mellon University
Speaker 1: would do very well in the next Grand Challenge. But
Speaker 1: that's a story we're going to cover in our next episode.
Speaker 1: Darpest statement was pretty darn positive. Quote. The Grand Challenge
Speaker 1: stimulated the creation of a new community of innovators, inventors, mechanics,
Speaker 1: computer scientists, engineers, and students who typically have not been
Speaker 1: involved in defense related activities. The camaraderie and competitiveness that
Speaker 1: have been the hallmark of the Grand Challenge since its
Speaker 1: inception demonstrates that America's heritage of ingenuity and resourcefulness is
Speaker 1: strong end quote. Now, in our next episode, we're gonna
Speaker 1: look at the Urban Grand Challenge of two thousand seven
Speaker 1: and how these competitions lead into the autonomous car environment
Speaker 1: that we are in today. And we'll also talk about
Speaker 1: some of the most difficult challenges we face, both technical
Speaker 1: and ethical. And we'll also talk about the pros and
Speaker 1: cons of driver list cars in our upcoming episodes, so
Speaker 1: I hope you look forward to those. It's been a
Speaker 1: lot of fun kind of going back through the history
Speaker 1: and seeing what has led up to what we see today.
Speaker 1: It's really fascinating to me to see the the transition
Speaker 1: away from a world where all of the autonomous nature
Speaker 1: of cars is built into the infrastructure surrounding cars to
Speaker 1: one where it's largely built into the vehicles themselves, and
Speaker 1: mostly because the Department of Defense needed innovation in that
Speaker 1: space in order to meet a deadline to have one
Speaker 1: third of all ground military combat vehicles automated by two
Speaker 1: fift we'll talk more about that as well in an
Speaker 1: upcoming episode. For the time being, if you guys have
Speaker 1: any suggestions for future episodes, or you've got any suggestions
Speaker 1: for people I should have on the show, or maybe
Speaker 1: there's just a topic that you've always wanted to know
Speaker 1: about Send me a message. The email address for the
Speaker 1: show is tech Stuff at how stuff works dot com.
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