Speaker 1: Ah, the information economy has a ride.
Speaker 2: The world is teeming with innovation as new business models
Speaker 2: reinvent every industry industry. Inside Analysis is your source of
Speaker 2: information and insight about how to make the most of
Speaker 2: this exciting new era. Learn more at inside analysis dot com,
Speaker 2: insideanalysis dot com. And now here's your host, Eric Kavanaugh.
Speaker 3: All Right, ladies and gentlemen, Hello, and welcome back to
Speaker 3: the only nationally syndicated show all about the information economy.
Speaker 3: It's called Inside Analysis. Your truly Eric Kavanaugh, and I'm
Speaker 3: very excited to be talking about one of the hottest
Speaker 3: topics out there. Who doesn't love a fun race car?
Speaker 3: Who doesn't love a software defined vehicle?
Speaker 1: What is that?
Speaker 3: What is a software defined vehicle? We're going to find
Speaker 3: out on the show today with a couple of experts.
Speaker 3: We've got Michael Franz from FPT calling in and also
Speaker 3: Florian Rhade who is with a company called Process. He
Speaker 3: used to work at Tesla, so he's done some cool stuff.
Speaker 3: He's out there in Las Vegas, so you know he's
Speaker 3: having fun. I mean, we live in Vegas. I mean,
Speaker 3: come on, it's twenty four to seven fund all the time.
Speaker 3: So we're going to talk about what's happening in the
Speaker 3: world of vehicles, and I think this is fascinating. I'm
Speaker 3: an old timer, so I had cars where you had
Speaker 3: to roll up the windows. You know, there's something special
Speaker 3: about that. If the fuse breaks, you could still roll
Speaker 3: the window down, so that's nice. But other than that,
Speaker 3: we like to have automatic windows and automatic gosh darn
Speaker 3: everything these days. I mean, the amount of innovation in
Speaker 3: this space is really quite remarkable. And obviously Elon Musk
Speaker 3: had something to do with that. Not everything, but he
Speaker 3: had something to do with it. And our guests are
Speaker 3: going to help us understand what is going on out there.
Speaker 3: So maybe Florian, I'll start with you. Tell us a
Speaker 3: bit about yourself and your company and how you got
Speaker 3: all into software divined vehicles.
Speaker 1: Yeah, thank you, Eric, and you got that right with Vegas.
Speaker 1: It's twenty four seven fun all the time. I've been
Speaker 1: in the automotive world for about twenty years now, and
Speaker 1: the most interesting window that started in twenty twelve when
Speaker 1: I joined a small company called Tesla Motors. It was
Speaker 1: a very small it was about two thousand people in
Speaker 1: the world, and we started building those cars. We never
Speaker 1: called them sdvs or software defined vehicles. We just decided,
Speaker 1: let's build a card the way we think a car
Speaker 1: should be from here on forward. And it turns out
Speaker 1: then at one point the industry labeled that SDVS. So
Speaker 1: I was at that company for six years almost and
Speaker 1: it was responsible for all the validation, so the testing
Speaker 1: of the software before it goes out of the development
Speaker 1: into the hands of the final of the end customers.
Speaker 1: And we signed off over seven hundred software releases in
Speaker 1: this six years. So it's a huge amount of software
Speaker 1: we got out. And yes, let me just pick up
Speaker 1: real quick with your window lifters, because electric windows are
Speaker 1: not SDV features, just to take that out of their way.
Speaker 1: There's EE features. That's the last generation of cars somewhere
Speaker 1: started in the early eighties, and we see that currently
Speaker 1: still out there. So those are actuated systems and they're
Speaker 1: controlled by microprocessors. Sdvs go one step further where you
Speaker 1: actually have a feature rich, updatable and upgradeable vehicle that
Speaker 1: is continuously improving at least, so it is the plan
Speaker 1: for the future from here on.
Speaker 3: Yeah, that's really interesting stuff. And you can you can
Speaker 3: adjust any number of things in that operating system, right
Speaker 3: because it's got a computer. I mean, lots of cars
Speaker 3: have had computers for a number of years, but not
Speaker 3: a very sophisticated computer. And this one is even more
Speaker 3: sophisticated than any of the ones that have come before it.
Speaker 3: Can you kind of walk us through what goes in there?
Speaker 3: What kinds of things can you update? Is it how
Speaker 3: the car is running? I mean you're actually affecting fuel,
Speaker 3: oxygen levels or something. Get into the details for us.
Speaker 1: So the cool thing is you actually already talk about
Speaker 1: the next generation of SDV. So what we see currently
Speaker 1: is that you actually have the controllers, the computers in
Speaker 1: the car working together. This is the first generation of
Speaker 1: an SDV, so you still have distributed computers in the car,
Speaker 1: only one, but they are starting to work on things together.
Speaker 1: So you have features and functionalities that are provided by
Speaker 1: several computers in together. And I have a very simple
Speaker 1: example from my Tesla times when they came up with
Speaker 1: a feature that you can use your microphone from your
Speaker 1: Bluetooth speaker set to talk to the people outside of
Speaker 1: the car through the pedestrian speaker wanting speaker. So those
Speaker 1: systems were never designed to work together, and those systems
Speaker 1: were never interconnected with each other, but with software defined
Speaker 1: vehicle functionality, they were actually able to make them work
Speaker 1: together if that feature is really necessary, not as a
Speaker 1: different question, but they make them make them work together
Speaker 1: and provided an over the air software update similar to
Speaker 1: what you know from your cell phone into the car
Speaker 1: to offer you that new feature. The next generation will
Speaker 1: be what we call HPC, so high performance computers, which
Speaker 1: you can basically assume it is like a central computer
Speaker 1: from this some logistics in the car. That is probably
Speaker 1: going to be more like to one in the front
Speaker 1: and one in the rear of the car because of
Speaker 1: the harness and the wiring issues, but in general that
Speaker 1: will be the next thing, and you can in very
Speaker 1: very simplified ways. You can think about your four eighty
Speaker 1: six IBM computer where you had to put all the
Speaker 1: stuff together that it works to your laptop you're probably
Speaker 1: looking into right now that is out of the box,
Speaker 1: and you know you have shared memory between the graphics
Speaker 1: driver and the hot drive and the process on this
Speaker 1: kind of stuff. So that is in a very simplified
Speaker 1: way where we are going.
Speaker 3: Yeah, and a lot of the features do revolve around safety,
Speaker 3: right like on keeping you in your lanes, alerting you
Speaker 3: doing things of this nature. And I think there's been
Speaker 3: a lot of advancement in the last few years of
Speaker 3: identifying what is a bicycle nearby, what's a car coming
Speaker 3: at me? What are these things? Because obviously the car
Speaker 3: has to identify this and then act in real time.
Speaker 3: You can't be you know, can't wait for an overnight
Speaker 3: update when something's coming at you, right.
Speaker 4: Yeah.
Speaker 1: And one of the reasons is because the compute in
Speaker 1: cars is growing significantly. So what the features you just mentioned,
Speaker 1: They need a lot of compute power in order to
Speaker 1: do the vision and the perception and then the reaction
Speaker 1: based on that. And we see this catching up in cars.
Speaker 1: You have seen much higher compute power already in domestic
Speaker 1: appli and applications like computers and so on. But cars
Speaker 1: is a little different, beast, because they can be outside
Speaker 1: at minus forty degrees celsius and they can be outside
Speaker 1: at at here in Vegas we topped out at forty
Speaker 1: seven degrees celsius one hundred and seventeen fahrenheit I believe,
Speaker 1: so your cell phone will not work in either of
Speaker 1: those conditions. So this is why the car industry is
Speaker 1: a little behind. And this is maybe where Mike can
Speaker 1: chip in a little bit from punintended from the chip
Speaker 1: side of things, because it takes a little bit longer
Speaker 1: to make those high performance compute chips ready for those
Speaker 1: environments cars are used in.
Speaker 3: Yeah, that's a good point. I did some work with
Speaker 3: the Electric Racing Association over in Europe a couple of
Speaker 3: years ago. It was a lot of fun. I mean,
Speaker 3: those electric cars are super fast, and the young kid,
Speaker 3: the driver, who is such a neat guy he had
Speaker 3: he gave me the headline with the article. He said,
Speaker 3: we have all the torque all the time. I was like, oh,
Speaker 3: that's the headline right there. And he's such a wonderful man.
Speaker 3: But I learned that there was a race in Spain
Speaker 3: where where they had to cancel it because it was
Speaker 3: too darn hot and the vehicles just wouldn't run. So
Speaker 3: I'll throw it over to Michael. The real world can
Speaker 3: be brutal out there from heat to cold. I mean,
Speaker 3: you're in the Detroit area.
Speaker 4: In Michigan, so yeah, we're kind of about to start
Speaker 4: going through some things. And yeah, Eric, you're right. The
Speaker 4: vehicle environment is not monolithic. It's not in an air
Speaker 4: conditioned environment. Ninety eight percent of the time, we have
Speaker 4: various applications and conditions that are that the vehicles we
Speaker 4: know and love have to operate in. That's why for
Speaker 4: years manufactures of tested in arctic conditions, they're tested in
Speaker 4: desert conditions, because they have to make sure that the
Speaker 4: that the integrator of the vehicle and everything that's in
Speaker 4: it can operate in a multitude of environments before it
Speaker 4: goes on the road. It's it's not good enough to
Speaker 4: launch it worth an application and so okay, well we'll
Speaker 4: worry about that future or feature set in the next update,
Speaker 4: in the next after ninety deaths, it's difficult to operate
Speaker 4: in those environments like that, and and of course that's
Speaker 4: where that's where the adeation meets the reality oftentimes in
Speaker 4: the automotive industry, where where you can you can market
Speaker 4: and position a product or a brand in a certain
Speaker 4: in a certain way, and then the regular does have
Speaker 4: to come in and say, well, guys, this is actually
Speaker 4: what you've got, and this is why we classify it
Speaker 4: as X Y Z right. And that's important because at
Speaker 4: the end of the day, it's still a three ton
Speaker 4: weapon in the wrong hands and needs to operate in
Speaker 4: a very safe condition and of course, the more we
Speaker 4: expose h cos to software, the more we have to
Speaker 4: secure them because this is this this becomes the next
Speaker 4: problem because as you open and expose yourself to the technology,
Speaker 4: so you open and expose your product and your service
Speaker 4: to bad actors around the planet. And again, not all
Speaker 4: vehicles are created equal, right uh, and thever will be there,
Speaker 4: there will be there will be manufacturers who will launch
Speaker 4: soft and defined vehicle technologies that are not as secure
Speaker 4: as everybody else's. And I'll give you a classic example
Speaker 4: right from from wayback, the Volve passenger car brand. When
Speaker 4: I say Vulbert, most people think of safety, and it
Speaker 4: would take an extraordinary amount of money for any other
Speaker 4: OEM to ever go and climb that mountain and say
Speaker 4: we're safer than a Volve that that people just don't
Speaker 4: do it. It's the same around software development, right The manufacturers
Speaker 4: that are SUSPI personally, the manufacturers that take care of
Speaker 4: the security and the securitization of their product as they
Speaker 4: launch their feature sets and software will ultimately win the
Speaker 4: race because we will we will unfortunately, see something's happened
Speaker 4: as as as this technology matures and goes into the industry.
Speaker 3: Right well, and that is I mean, you bring up
Speaker 3: an excellent point because you know and I often sit
Speaker 3: and think about this stuff, security and protocols and technologies,
Speaker 3: and of course the keybob comes along. And that's great
Speaker 3: because you can find your car in a parking lot.
Speaker 3: But if you lose your keybob, so can the bad guy.
Speaker 3: If you describe your keybob and walk around the park
Speaker 3: and I go beepep up there it is I go
Speaker 3: steal that pull.
Speaker 4: We all know that the nightmare stories already of things
Speaker 4: like key fobs that are that are not secured in
Speaker 4: the security code hopping where we're bad at this can
Speaker 4: can jam the signals, copy them and then open your
Speaker 4: vehicle and drive right. This is not new. This has
Speaker 4: been in the industry for many, many years, and it's
Speaker 4: as the simplest function today. Pick the button, open the
Speaker 4: vehicle right or lock the vehicle and proximity to the
Speaker 4: vehicle full timelindow. All of those things really present a risk,
Speaker 4: and that's no technology right. So we have to we
Speaker 4: have to take care of all of these things in
Speaker 4: a responsible way, and we have to take care of
Speaker 4: it in a multitude of places and times and locations.
Speaker 4: And geographies, and technology stacks and things like mobile networks
Speaker 4: that run on different frequencies. The vehicles have to talk
Speaker 4: on multiple frequencies in different geolocations to the back end
Speaker 4: and from the back end to itself. So it's it's
Speaker 4: it's a complex world, and we have and manufacturers and
Speaker 4: the Tier one partners have a responsibility to look after
Speaker 4: the vehicles that are already on the road for a
Speaker 4: number of years, and they have to play for the
Speaker 4: future at the same time. So it's a huge responsibility idea.
Speaker 3: Yeah, that's a really good point because you do have
Speaker 3: this entire arc of legacy vehicles out there. I mean,
Speaker 3: you've got cars from the nineteen forty still driving around.
Speaker 4: And the reality, the reality on the road is today
Speaker 4: in America, the average vehicle is twelve points something years old.
Speaker 4: People are keeping the year their cars longer and longer
Speaker 4: because affordability is an issue, you know, the economic climate's
Speaker 4: an issue, right, we have to acknowledge these things. We
Speaker 4: must push forward. But the reality on the ground is
Speaker 4: that the vehicles we even introduce today are probably going
Speaker 4: to be around for more than ten years, and somebody
Speaker 4: has to take care of all of that technology stack
Speaker 4: as it goes forward, you know the in it we
Speaker 4: talk about technical debt in terms of in terms of
Speaker 4: aging infrastructure and aging technologies. I believe that the industry
Speaker 4: will needs to take care of the of the when
Speaker 4: you say technical deat of today's vehicles twelve years from now,
Speaker 4: because the vehicle in twelve years from now will look
Speaker 4: very different to what it is today.
Speaker 3: Well, and that's I would sorry, I would argue I'm
Speaker 3: more afraid of the vehicles of last year than I'm
Speaker 3: afraid of the vehicles from thirteen years.
Speaker 1: Ago from security point of view.
Speaker 4: Because absolutely, that's why my car that I owe, not lease,
Speaker 4: is genious.
Speaker 1: Yes, So it's as soon as the vehicles start to
Speaker 1: become a member and a participant at communication that goes around,
Speaker 1: like we call this V two X or a vehicle
Speaker 1: to everything or vehicle to vehicle v t V. This
Speaker 1: is where security actually has to go a whole level
Speaker 1: up because my vehicle can now tell Mike's vehicle to
Speaker 1: slim the brakes for a variety of reasons, and if
Speaker 1: I have an malicious attack planned on Mike, I can
Speaker 1: just tell his car to stop. Obviously, this is a
Speaker 1: very simplified example and It is not that easy. But
Speaker 1: there are those things, and it is the fact that
Speaker 1: this technology is out there is Mike mentioned, and it's
Speaker 1: available not only for car makers, it's also available for
Speaker 1: people who have bad ideas around cars. So I would
Speaker 1: even argue they are ahead from the technology point of
Speaker 1: view compared to the carmakers and OEMs right now from
Speaker 1: security point of view.
Speaker 3: Wow, that's interesting. And you know, you remind me of
Speaker 3: something that I think is quite fascinating because these cars
Speaker 3: are instrumented, and so you're gathering data from various points
Speaker 3: like the break and the engine in other places like that.
Speaker 3: I'm guessing that is incredibly valuable data for the next
Speaker 3: generation of car design, right for being able to optimize
Speaker 3: the wheels or the drive train or whatever the case
Speaker 3: may be. Having that just massive treasure trove of data
Speaker 3: coming in from the vehicles that's got to be fun
Speaker 3: to work with, right.
Speaker 4: Yeah.
Speaker 1: So the fact is that as an engineer, you only
Speaker 1: know that you if you underdesigned your product, if you
Speaker 1: overdesigned it, you never know because it will never come
Speaker 1: back to you.
Speaker 4: Right.
Speaker 1: So they come back to service when something breaks, but
Speaker 1: if they never come back to service, you don't know.
Speaker 1: If you reached ninety nine percent of the capability over
Speaker 1: lifetime or one percent, and one percent is a nightmare
Speaker 1: because that means you completely overpaid the development of that product.
Speaker 1: And we had at Tesla, we had those situations where
Speaker 1: we actually looked at the data and we actively took
Speaker 1: that information into consideration for cost downs and for next
Speaker 1: generation vehicles, to not only make those things that broke
Speaker 1: more sturdy and better for the next generation, but also
Speaker 1: make those things that were completely overdesigned and therefore also
Speaker 1: probably too heavy light more lightweight and better suited for
Speaker 1: electric vehicles. But I have to say as well, depends
Speaker 1: on where you are in the world. There's huge discussions
Speaker 1: who owns that data. Is it the owner of the
Speaker 1: car who creates that data by driving the car. Is
Speaker 1: it the maker of the car, who you know, collects
Speaker 1: the data in your car. Is it maybe a mixture
Speaker 1: of that. So that has not concluded yet that discussion.
Speaker 4: And Florin has been a great engineer by saying, you
Speaker 4: want to collect all the data all the time, of course,
Speaker 4: and of course I always count to that by saying
Speaker 4: and right now, because we're building it out and we're
Speaker 4: discovering new things. The engineers are driving that push for data.
Speaker 4: How much of that data is really needed when the
Speaker 4: vehicle is launched, Right, at what point do we have
Speaker 4: to say, well, not every thing is that needs to
Speaker 4: be available real time live. Certain things have to be
Speaker 4: other things can may be stored and up later because
Speaker 4: at the moment the amount of data is exponentially ten
Speaker 4: xing the more the more technology put in the vehicles,
Speaker 4: and the more the it's algorithm based in in terms
Speaker 4: of what are the performance of the vehicle, you know,
Speaker 4: et cetera.
Speaker 1: So AND's a there's a very simple example because the
Speaker 1: car communicates the exterior temperature with one hundred hertz inside
Speaker 1: the car, but you don't have changes in the temperature
Speaker 1: within milliseconds, so you don't really have to collect that
Speaker 1: data on a ten millisecond base, right, every ten minutes
Speaker 1: is enough. That's a very simple example. Everybody can grasp.
Speaker 3: No, that's a good point. And you know we're coming
Speaker 3: up on the end of this first second here in
Speaker 3: just a minute. But what I think is really fascinating
Speaker 3: is the whole design process and how all these different
Speaker 3: parts have to come together. And so you talk about
Speaker 3: something having been over engineered or it's too heavy, or
Speaker 3: it's too expensive. You know, these days, we're getting to
Speaker 3: the point where you really can map out and understand
Speaker 3: how much time it took to build this part or
Speaker 3: that part, what the parts cost themselves. My point is like,
Speaker 3: we're so much better today than we were probably even
Speaker 3: twenty years ago in terms of being able to really
Speaker 3: understand what is the total cost of ownership, what is
Speaker 3: the cost of all the personnel who went into the
Speaker 3: design phase to get us to this next stage? And
Speaker 3: how do you prioritize That's what I'd love to understand
Speaker 3: is as you as you roll out one one car,
Speaker 3: the twenty twenty five version, I'm sure immediately the engineers
Speaker 3: are already thinking to the twenty twenty six version, you know,
Speaker 3: what should we change for that? Do weeople want more
Speaker 3: do they want a better gas mileage? Do they want
Speaker 3: better comfort?
Speaker 4: You know?
Speaker 3: And then knowing like how to compartmentalize all that stuff,
Speaker 3: that's got to be a fascinating series of meetings and
Speaker 3: discussions and decisions that are made to determine you have
Speaker 3: to hit certain deadlines and okay, this is why it's
Speaker 3: going to be for next time. Well, folks, don't touch
Speaker 3: that that'll be right back by a fantastic conversation about
Speaker 3: software divined vehicles. You're listening to Inside Analysis.
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Speaker 2: Welcome back to Inside Analysis. Here's your host, Eric Tabanac.
Speaker 3: All right, folks, back here on Inside Analysis, talking all
Speaker 3: things software divined vehicles. We've got Michael Franz on the
Speaker 3: line from FPT and Florian Road from IE Process and
Speaker 3: we're just chit chatting about what goes into all this.
Speaker 3: The decision making process and decoupling came up as a
Speaker 3: as a key topic to dive into, so I'll throw
Speaker 3: it over to Florian first. When you say decoupling software
Speaker 3: from hardware, what do you mean by that?
Speaker 1: So originally cars were designed mechanical, electrical, and software, and
Speaker 1: this all came together to what we call SOP the
Speaker 1: start of production, and then you basically deliver that car
Speaker 1: to you know, the dealerships. They start selling that for
Speaker 1: a couple of years and you and your engineering team
Speaker 1: in all those three branches start over for the next
Speaker 1: generation and continueually. At Tesla we started this decoupling completely,
Speaker 1: so the new vehicles are inheriting the software of the
Speaker 1: other vehicles. So basically what you see out there in
Speaker 1: Tesla is one software platform that okay, it's a little
Speaker 1: bit of configuration is different per car, but in general
Speaker 1: there's one software platform that runs on all their cars,
Speaker 1: so it's decoupled from the actual version of the car.
Speaker 1: So a Model ass and a Model three is technically
Speaker 1: the same software with certain varieties in there. And so
Speaker 1: like this, when your car gets into a next generation,
Speaker 1: from mechanical point of view, your software is actually not
Speaker 1: waiting those four years for that. It's continuously evolving and
Speaker 1: is then applied to new platforms that are going out.
Speaker 1: So and therefore it's the software and the hardware is
Speaker 1: decoupled from each other.
Speaker 4: That's greatl and Eric just just the layer on top
Speaker 4: of that. We used to have in this industry an
Speaker 4: eight to ten year window of a vehicle, and round
Speaker 4: about four or five years you get a midlife cycle
Speaker 4: impulse or a mid life cycle update with the manufacture
Speaker 4: which changes the front bumpers. They change the light a
Speaker 4: little bit on the outside. You may get a couple
Speaker 4: of pain configurations, maybe one or two more interiors, and
Speaker 4: instead of the last year or two of that vehicle,
Speaker 4: you get the full house, right the manufacturer throw the
Speaker 4: full month you hated, all the options you were paying
Speaker 4: for before, and now built in because now they want
Speaker 4: to move the metal and you suddenly you get the
Speaker 4: best wheels and entire packages, You get the best engines,
Speaker 4: and off it goes and they ride that vehicle into
Speaker 4: the sunset. Because in the background, over the last eight
Speaker 4: to ten years, the engineering and design teams have been
Speaker 4: working on the new version right and suddenly you get
Speaker 4: to the current situation in the market right now, where
Speaker 4: the pressure is on and the OEMs have all turned
Speaker 4: around inside themselves trying to figure out, how do we
Speaker 4: get to release a vehicle in eighteen months from scratch
Speaker 4: or a blank piece of paper because manufacturers in China
Speaker 4: are doing it. How are they doing it? How is
Speaker 4: this possible? And what Florida talks about into the decoupling
Speaker 4: a software attack is exactly that they use the same
Speaker 4: software platform. It's almost like using a software platform to
Speaker 4: build a home appliance, and you can and you can
Speaker 4: generate four or five brands or looking different, but they
Speaker 4: all do essentially the same thing. This is the way
Speaker 4: that the industry is moving, and this is causing pressure
Speaker 4: in the market because in the industry, because the need
Speaker 4: is accelerating to launch new product faster and faster at
Speaker 4: lower cost, and based only on the fact that you
Speaker 4: can redesign the shell in the vehicle basically and some
Speaker 4: of the underpinnings and the performance, but the software driving
Speaker 4: that vehicle is actually similar, very similar, ninety eight percent
Speaker 4: copy in.
Speaker 3: Yeah, that's that's very cool stuff. And I'm guessing that
Speaker 3: you've got some good digital twin software out there, right
Speaker 3: to design the new cars and to kind of test
Speaker 3: them in a virtual world and see what happens.
Speaker 4: Right, canors?
Speaker 1: Yeah, Well, the term digital twin is used for actually
Speaker 1: a variety of things, right, So there's no one digital twin.
Speaker 1: So some people hear that and say, oh, this is
Speaker 1: just like a simulated car. You can just like see
Speaker 1: it through the three D you know, glass something like this.
Speaker 1: But there's a variety of digital twins. There's much much
Speaker 1: more simpler ways out there, where you just have certain
Speaker 1: models or certain algorithms and you test them all the
Speaker 1: way up to like packaging digital twins, where you figure
Speaker 1: out can that seat move enough to the back without
Speaker 1: you know, hitting the knees of the person behind you.
Speaker 1: There's a very different digital twins. So they're very purpose built.
Speaker 1: And the short answer to your question is yes, there's
Speaker 1: a lot of software simulated parts or versions of that vehicle.
Speaker 1: And I to go back to some anecdotes. I remember
Speaker 1: it was long time ago, so ten years ago. I
Speaker 1: saw Elon Musk with some Oculus rift thingy handing around
Speaker 1: in the air, and so he was checking out the
Speaker 1: Model X design in a virtual environment, and that we
Speaker 1: couldn't see because he was just sitting in the middle
Speaker 1: of the office and waving his arms around. So it
Speaker 1: was hilarious. But this is where we are going, right,
Speaker 1: So the the design and the packaging and all that
Speaker 1: stuff that is going all virtual before it goes in
Speaker 1: crash testing. We did crash testing ninety nine percent in simulation.
Speaker 1: The first car, the first Model three. I believe that
Speaker 1: crashed was at the crash test facility for the actual certification,
Speaker 1: so we didn't crash any of that before and it
Speaker 1: was spot on with the simulations. So in software. We're
Speaker 1: actually doing this as well now, so we have software
Speaker 1: environments virtual ECUs. It is one of the buzzwords this
Speaker 1: year in the industry where you can test your software
Speaker 1: without the hardware. And this is where it's getting really
Speaker 1: important you integrate it with other pieces of software and
Speaker 1: with other pieces of the car, because this is where
Speaker 1: we see the most challenging challenges. It's getting more complex,
Speaker 1: it's getting more fun and interesting, but integration is the
Speaker 1: large challenge we are all facing. So simulation is helping
Speaker 1: us a lot there.
Speaker 4: Yeah, I'll give you another. I'll give you another ideaic.
Speaker 4: Driver monitoring, right, there's a legislative push to get driver
Speaker 4: monitoring more and more into vehicles going forward. This is
Speaker 4: camera tech watching your eyes and and and the camera
Speaker 4: can tell when you're getting drowsy based on certain tael
Speaker 4: points better than any better than your your life partners
Speaker 4: sitting in the in the in the seat based a
Speaker 4: right that they're watching the speed of how you're blinking
Speaker 4: your eyes, how long your eyes are closed in a blink,
Speaker 4: and that's triggering the warning signals to to to pull
Speaker 4: over and stop the vehicle right now. In order for
Speaker 4: that to get tested, it would take hundreds of thousands
Speaker 4: of hours of a guy or a girl behind the
Speaker 4: wheel of a car driving around the pill they're literally
Speaker 4: starting to pass out. Simulating that monitoring is a is
Speaker 4: a deal breaker in terms of in terms of getting
Speaker 4: that technology to get passed and implemented safety into vehicles.
Speaker 4: And it's a it's a crass critical component, right, you
Speaker 4: need to be able to have this, And I think
Speaker 4: it's a fantastic idea that that the driver monitor is
Speaker 4: not to monitor you and what you're doing. It's to
Speaker 4: monitor that you're not pulling a steep behind the wheel.
Speaker 4: And and if we have the capability to do that,
Speaker 4: then for me, I believe those are those are features
Speaker 4: and functions that are all great to him.
Speaker 3: Well, and it is great, you know. It's like when
Speaker 3: I go to the airport. Sometimes I get annoyed by
Speaker 3: going through all the security stuff, but it's like the
Speaker 3: argument is, hey, if we catch one person who was
Speaker 3: trying to do something bad, it's worth all the effort.
Speaker 3: It's the same in the car industry because let's fax
Speaker 3: it man, Like you said, it's a two three thousand
Speaker 3: pound weapon if it's not managed properly. And so that's
Speaker 3: why these safety features are so valuable and so important,
Speaker 3: and that's good stuff because you know, people they push
Speaker 3: the envelope. I've been there myself. I'm driven longer than
Speaker 3: I should have when I started getting tired trying to
Speaker 3: make some hail, you know, while the sun is shining,
Speaker 3: and then you get that little warning ding ding ding.
Speaker 3: It's like, okay, I do need to pull over. That's
Speaker 3: when life's like I told you, let's pull over.
Speaker 1: Yeah, Eric, after one second, like yeah, Eric, I have
Speaker 1: to give you a quick dose of reality. Our cars
Speaker 1: are not two three thousand pounds double that oh wow.
Speaker 4: And heavy because are the badges? Right? But Eric, I
Speaker 4: think it's going to go further than just the coffee
Speaker 4: cup on the dashboard right that, that's where it started.
Speaker 4: You don't time to take a break because it's timing
Speaker 4: how long you've actually been running in the vehicle. It's
Speaker 4: going to it's going to get to a point where
Speaker 4: the vehicle is going to going to take over you
Speaker 4: aside and into a safety zone and switch off. Right.
Speaker 4: Not because people ignore the safe round right, I mean
Speaker 4: we have we have we have maximum speed limit signs
Speaker 4: all over the place, and do people listen to it? No,
Speaker 4: they don't. They're local it, they don't accept it. They
Speaker 4: just do whatever they want to do. So so so
Speaker 4: I think it's important, and I think it's even it's
Speaker 4: it must be pervasive in the industry, that type of solutioning,
Speaker 4: especially heavy duty trucks. You know, we move seventy odd
Speaker 4: percent of our freak by road in North America. We
Speaker 4: need to really think about those kinds of things and
Speaker 4: and say, hey, mister driver, I know that you're allowed
Speaker 4: X number of hours per per week or per month
Speaker 4: on the road, but actually, on this specific trip, you
Speaker 4: are actually starting to do those or let's get you,
Speaker 4: let's get you safety pulled to the side so we
Speaker 4: can sort that up, you know. And I think that
Speaker 4: that that kind of check out us, right.
Speaker 3: Yeah. Well, and it's like I've been fascinated just in
Speaker 3: my own life noticing what algorithms can notice about you,
Speaker 3: like your behavioral patterns. People don't realize how transparent they are, frankly,
Speaker 3: but a machine is just monitoring behavioral patterns, and those
Speaker 3: patterns of getting drowsy are pretty significant and pretty clear,
Speaker 3: and so it's wonderful. I mean, you can't really calculate
Speaker 3: how many lives are saved, but you know for sure
Speaker 3: that lives are being saved, right.
Speaker 1: And it's not only that right. Also as a medical emergency,
Speaker 1: for example, I'm not only assuming that people does away
Speaker 1: behind the wheel, but there's also people have medical emergencies.
Speaker 1: And just to close the loop, I think this is
Speaker 1: a great example of SDV as well, because you have
Speaker 1: a camera feature that the texts that there is something
Speaker 1: wrong with the driver. It then hands over that information
Speaker 1: to the autonomous driving feature set off the car, which
Speaker 1: then together with the map system and with the cameras
Speaker 1: outside of the car, safely pulls that car over and
Speaker 1: starts an e call to bring you to medical service
Speaker 1: you need. So this is a it's a simple but
Speaker 1: good example how things work together even though they are
Speaker 1: separate parts of the car.
Speaker 3: Yeah, that's an excellent point because people do have a
Speaker 3: cardiac arrest or a stroke and a number of things
Speaker 3: can happen, and if your vehicle can then take over
Speaker 3: and understand what's happening, move you to the side, get
Speaker 3: you so you're not going to harm yourself or someone else,
Speaker 3: and then exactly call the the you know, call the
Speaker 3: paramedics to come get you. And that is a wonderful
Speaker 3: confluence of technologies to help preserve people lives and of
Speaker 3: course the car too, right because you know, if someone
Speaker 3: falls asleep behind the wheel man, whoo, it goes back
Speaker 3: real fast. Yeah fast.
Speaker 4: If eighty miles an hour down a Tennessee highway and
Speaker 4: that happens, they could do some trouble, right.
Speaker 3: Oh yeah, Well, and you know, just the other day
Speaker 3: we're driving back. In fact, last night I was driving
Speaker 3: and you hit the bump like that, and my daughter
Speaker 3: is like, why is it doing that? I said, because
Speaker 3: it's warning you as you're going around a curve and
Speaker 3: you don't want to be in the oncoming lane around
Speaker 3: a blind I was very proud of myself when my
Speaker 3: daughter picked up what a blind curve is?
Speaker 1: Yes, this is a very analog feature. You encount that there.
Speaker 1: We're working on the digital version of that.
Speaker 3: That's funny. It's a very analog feature. And you know
Speaker 3: blind turns. I mean, all it takes is one accident
Speaker 3: when you're younger to really appreciate the significance of an accident,
Speaker 3: of a car accident. And I'm on the count of guy.
Speaker 3: When I'm driving, I'm always thinking, and then there's a
Speaker 3: blind turn. Like, be careful, man, because you never know
Speaker 3: someone could be losing control. There could be an ice
Speaker 3: patch or something. And you know, if you're in a
Speaker 3: small car like my Miata and some dump truck comes
Speaker 3: around that corner, man, let me tell you it's gonna be.
Speaker 1: This brings us back to what I said earlier to
Speaker 1: vehicles to vega communications. So if you have those blind
Speaker 1: turns right in the car in front of you and
Speaker 1: counted the ice patch, it will actually tell your car,
Speaker 1: not your Miata, but your connected car will get that information.
Speaker 4: Right.
Speaker 3: That's so where this is a good topic to dive into.
Speaker 3: How far along are we in that vehicle to vehicle communication.
Speaker 3: So if you have two new Teslas, for example, what
Speaker 3: you're saying is that they and how do they sense?
Speaker 3: Is it a sort of a GPS driven thing that knows, okay,
Speaker 3: you're now in my vicinity and you know you're coming
Speaker 3: around a turn like can all those factors actually get
Speaker 3: processed in real time to trigger a warning like that?
Speaker 4: Yeah?
Speaker 1: So first, I think we are already at a very
Speaker 1: good point within a certain brand. So tesla to tesla
Speaker 1: I think is much more evolved than folks who wanting
Speaker 1: to BMW or something like this, because they are still
Speaker 1: working on as on some standards because they have to
Speaker 1: speak the same language so to say right, but in
Speaker 1: general yes, you're correct. So there is something we call geofancing,
Speaker 1: so they know which area they are and they're basically
Speaker 1: similar to your cell phone. They just book into look
Speaker 1: I'm in this area. Now I'm driving through San Francisco,
Speaker 1: and then it's it's actually called CV two X or
Speaker 1: cellular vehicle to Everything. So this is when the cars
Speaker 1: use the cell network to go basically through a satellite
Speaker 1: or through I mean not an actual satellite up there
Speaker 1: as a sort of server and talk to the other car.
Speaker 1: And the other thing we also we will see within
Speaker 1: the next few years is how they talk to the infrastructure.
Speaker 1: So the red light communicates the status of a red
Speaker 1: light to your car. That can reduce your consumption because
Speaker 1: your car will actually on out a pilot will slow
Speaker 1: down earlier and come to a stop without wasting energy.
Speaker 1: Stuff like this. So this is happening in controlled environments
Speaker 1: and in smaller patches already. Over the next five to
Speaker 1: ten years, we will see that rolling out really in
Speaker 1: a way that everybody realizes it and as a simple
Speaker 1: add on on that. So I have a friend who
Speaker 1: runs a company who works to get green lights for
Speaker 1: emergency vehicles, and I say, wow, but you would have
Speaker 1: to get every light online. This will take you one
Speaker 1: hundred years. And he said no, you know, actually where
Speaker 1: you live in Las Vegas, more than ninety percent of
Speaker 1: the traffic lights are online already. Yeah, so we don't
Speaker 1: know because we don't focus on that technology, right, But
Speaker 1: a lot of environments, metal technology is already ready for
Speaker 1: all of the stuff we're talking about. So it's it's
Speaker 1: it's getting there. It's about to get it all together.
Speaker 4: I'll give you another example, Eric, there's there's currently a
Speaker 4: rollout of a program for emergency services to notify certain
Speaker 4: brands of vehicles that they are in proximity of an
Speaker 4: emergency vehicle. It's coming up behind you or to your left,
Speaker 4: or to your right or in front of you, based
Speaker 4: on your orientation of the vehicle. That kind of that
Speaker 4: kind of technology, I believe is really a great example
Speaker 4: of using that cellular down to single cell information and
Speaker 4: repeating it across across even a different brand. I mean,
Speaker 4: it'll be a fire truck telling or whatever product that
Speaker 4: that's coming as soon as that becomes pervasive. That type
Speaker 4: of thing is great because it starts to clear the
Speaker 4: emergency lane, make the vehicles pull over the way they
Speaker 4: should pull over. You're you're not looking around rubbernecking to
Speaker 4: figure out where is the firetruck or the ambulance because
Speaker 4: nobody can ever tell, but you know it's behind you
Speaker 4: and it's approaching, right. So that's a simple example of
Speaker 4: that vehicle to x that vehicle to anything environment and
Speaker 4: how that is going to start becoming more and more
Speaker 4: of evasive as it goes along. Of course, it's very
Speaker 4: difficult to get things like in the built environment to
Speaker 4: talk to the vehicles, or as simple example is who
Speaker 4: owns the traffic light and the data coming in and
Speaker 4: out of the traffic light?
Speaker 3: You know, yeah, yeah, yeah, we'll pick us out of
Speaker 3: the break Folks, don't touch up down or you're listening
Speaker 3: to in someone elsis interciting.
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Speaker 2: Welcome back to Inside Analysis. Here's your host, Eric Tabanac.
Speaker 3: All right, folks, back here on Inside Analysis talking to
Speaker 3: a couple experts in software divined vehicles. Such cool stuff
Speaker 3: out there, and I'll throw it over maybe to Michael
Speaker 3: first and then to Florian. I remember learning this ultimate
Speaker 3: sales pitch for self driving cars, and that is no
Speaker 3: more traffic jams, right, because if you can orchestrate, if
Speaker 3: you can orchestrate every vehicle in this environment, you won't
Speaker 3: have the darn traffic jams anymore. I mean you can
Speaker 3: at least expedite traffic at high peak times to get
Speaker 3: through difficult periods of time, because who likes a traffic jam.
Speaker 3: Nobody likes a traffic jam, nobody. I can't live in
Speaker 3: traffic jams. I'd lose my mind in a traffic jam.
Speaker 3: I will pull over and do something else for an
Speaker 3: hour to not have to sit there in a traffic jam.
Speaker 3: But go ahead, what do you think, Mike?
Speaker 4: And you're going to continue pulling over to do something
Speaker 4: else while do you experience the traffic jam for probably
Speaker 4: as long as you and I still have a valid
Speaker 4: driver's license. And the reason for that is because it's
Speaker 4: the simple er physics. Right. Two, Our solid objects cann't
Speaker 4: occupy the same space at the same time, godless of
Speaker 4: the algorithm. Right. The bottom line is we are still
Speaker 4: working eight to five as you were in the industrial age,
Speaker 4: when we are way past information age. And this is
Speaker 4: the reality that we are all we all signed up for. Right. So,
Speaker 4: if you're in Washington and you have in DC, and
Speaker 4: you have to do that run in that side of
Speaker 4: the world. If you're in Dallas Fort Worth, you have
Speaker 4: to do those run in Atlanta. It's not going to
Speaker 4: change because everybody's still on the road. Right. We may
Speaker 4: smooth out the edges, we may we may save a
Speaker 4: couple of minutes, but the bottom line is a reasonable
Speaker 4: I will work at five and at home and try
Speaker 4: and be onn by six six thirty. And that means
Speaker 4: that a million people need to be on the road
Speaker 4: at the same time. That's right. And we hopefully we
Speaker 4: have less accidents, which we use the lane stale pit
Speaker 4: which means it's pits mud and and and hopefully we
Speaker 4: come to our interne with society and go in the
Speaker 4: information age to be really all left to knock off
Speaker 4: at the same time, can we can we maybe think
Speaker 4: a little differently about the work living, you know, But
Speaker 4: that's another story for another day. But that's yeah, the
Speaker 4: bottom line is and and if you've ever been just
Speaker 4: like Bengal or Delhi, you know that there's no way
Speaker 4: that that fully autonomous vehicle is going to solve any
Speaker 4: traffic problems in that part of the world in any
Speaker 4: time soon. Right. So that's that's funny the way it is.
Speaker 1: I got a little bit of a ray of sunlight
Speaker 1: for you here, Eric.
Speaker 4: So it's so so first in the sales pitch.
Speaker 1: Yeah, so actually I've just picked up what Mike said.
Speaker 1: So there are a couple of different reasons why you
Speaker 1: have a traffic jam, right, So one of them is
Speaker 1: congestion due to a high frequency, a hi high number
Speaker 1: of vehicles at the same time. There Actually, yes, Mike's writer,
Speaker 1: can't occupy the same space with more than one vehicle,
Speaker 1: But we can reduce the space between vehicles, so that
Speaker 1: makes that a little better. We call it plattooning for example,
Speaker 1: So you have the vehicles communicating with each other, that
Speaker 1: takes out the need for the distance in between them,
Speaker 1: and you can have the basically like pearls on a string.
Speaker 1: Then the other thing, which is I think is much
Speaker 1: more important, is on accidents as a cause of a
Speaker 1: traffic jam, and that is our all common goal to
Speaker 1: reduce the accidents to a minimum by applying those features
Speaker 1: and functionalities in software and in the vehicles. And like,
Speaker 1: I don't know the percentage of traffic jams caused by
Speaker 1: accidents versus congestion, but I know that traffic jams caused
Speaker 1: by accident in combination with congestion are the worst. So
Speaker 1: we try, we try our best to get really the safety,
Speaker 1: and that's the number one on the sales pitch, right,
Speaker 1: it's safety, then it's comfort, and then it's you know,
Speaker 1: all the other stuff, and like that we reduce your
Speaker 1: promises traffic jams, hopefully by reducing a number of accidents
Speaker 1: on the road.
Speaker 3: No, that makes sense, that's good stuff. You're right that
Speaker 3: when you get an accident and you have congestion and
Speaker 3: all these things at once, and it's snowing outside or something,
Speaker 3: that's when it all kind of falls apart there. I'm
Speaker 3: curious to know, you know, Google and of course what
Speaker 3: is it? Weighs and some of these other apps are
Speaker 3: getting very good at being able to sense how many
Speaker 3: cars are in a certain area. You get these warnings
Speaker 3: on your phone. How much of that factors into what
Speaker 3: you guys work on. Are you able to tap into
Speaker 3: their system and understand how they do that. I know
Speaker 3: you talked about standards and protocols and things, but where
Speaker 3: are we in terms of really sharing that information even
Speaker 3: in real time at scale?
Speaker 1: I think traffic we are like there, so sharing traffic information,
Speaker 1: you can have that down to the granularity of a
Speaker 1: couple of meters. Other topics, it's a little tricky, but
Speaker 1: there's also sometimes there's contractual reasons. There is you know,
Speaker 1: non disclosure agreements and so on. But on the traffic
Speaker 1: side of things, I think we're spot on. It's available
Speaker 1: to you as an individual. It's the same available to
Speaker 1: your computer in your car, so they can do intelligent
Speaker 1: route planning, they can do intelligent charge planning, if you
Speaker 1: choose to go electric, they can take all this into consideration.
Speaker 1: So I think that's a great example of how collaboration
Speaker 1: should work, and it should actually work in other areas
Speaker 1: soon as well. But the traffic spot on already working.
Speaker 4: I think I think that the next generation overlay is
Speaker 4: really what I call what we call precise position in
Speaker 4: writing traffic. So at the moment your you're mapping technology
Speaker 4: that you use, probably Apple, Corplay or Android or Ways
Speaker 4: or whatever you're using, is telling you that you're driving
Speaker 4: down Main Street going north right, versus it's not telling
Speaker 4: you you're in lane two or three on Main Street
Speaker 4: and you and lane two means you must go straight right.
Speaker 4: So precise position is really getting that vehicle to be
Speaker 4: I can get you within centimeters or millimeters or less
Speaker 4: than an inch of where you actually are as a
Speaker 4: vehicle in those lanes because that that that starts to
Speaker 4: help you and the vehicle understand where when the autonomous
Speaker 4: LUs system or the system driving system says turned right,
Speaker 4: it knows you have to be in the right lane
Speaker 4: of three. And if you are not in the right
Speaker 4: lane of three and a cratical example, sometimes you're driving
Speaker 4: them already and you get a eglection the car things
Speaker 4: you at to McDonald's parking lot, any lot of the
Speaker 4: intersection right, that is not precise position. Precise posision means
Speaker 4: it got to know you're there right, And that's that
Speaker 4: could be done with a myriad of ways. It can
Speaker 4: be done by a satellite precise position overlayd of the
Speaker 4: fund network. It can be done by camera and light
Speaker 4: our sensing technologies based on other vehicles around in proximity
Speaker 4: to put you in the in the correct lane. And
Speaker 4: probably it will be a combination of all of that
Speaker 4: stuff as it goes forward, but that for me would
Speaker 4: be the next generation of precise positions. So and then
Speaker 4: it starts to help things like traffic congestion, because then
Speaker 4: the built environment says, oh, hang on, Eric has got
Speaker 4: fifty five guys in girls behind them in the right
Speaker 4: plane all trying to get into the stadium to watch
Speaker 4: the game. Let's open that turn right signal fifty five
Speaker 4: seconds longer per go so we can start to alleviate
Speaker 4: that cue. Right. And then we started to talk about
Speaker 4: smart systems live on the algorithm based solutioning. Right. I
Speaker 4: love that.
Speaker 1: I can't wait for that.
Speaker 4: That.
Speaker 1: Finally, the traffic lights are not just green for empty,
Speaker 1: you know. I have like literally like I'm waiting at
Speaker 1: a red light and there's tumbleweed coming through, and it's
Speaker 1: like why Right. But the good news Eric, here is
Speaker 1: everything that Mike was talking about is actually ready to go.
Speaker 1: So we see that rolling out already. So this is
Speaker 1: actually the state of the art on the R and
Speaker 1: D side of things. We are seeing this coming out
Speaker 1: with new generation cars, the traffic light shifting and or
Speaker 1: changing in my favor, I haven't seen that yet, but
Speaker 1: I'd like to see that soon.
Speaker 4: We can tray about it.
Speaker 1: Yes, but it's a good snapshot of where the technology
Speaker 1: is already.
Speaker 4: Yeah, what's possible? Right? Yeah? And Eric, the precise position,
Speaker 4: I'll give you another sort of example of where it's working.
Speaker 4: I never culture sector, So autonomous vehicles in agriculture is
Speaker 4: already pervasive. It needs to be because we need people
Speaker 4: to do work in large areas at the same time. Right,
Speaker 4: and when you're spraying crops with insecticides or with chemical enhancement,
Speaker 4: whatever you have to do on a farm, I don't know.
Speaker 4: There are legislative requirements around where you must stop and
Speaker 4: start the spraying the of those crops, and those are
Speaker 4: defined geographically as a very precise line. And when you
Speaker 4: use precise positioning, you can actually dictate where that spray
Speaker 4: actually starts and stops autonomously already because the vehicle can
Speaker 4: recheck to that level because they can map those areas
Speaker 4: very well. So it's just to give you an idea
Speaker 4: of how that technology can really overlay right into adjacent industries.
Speaker 3: Well, that's good stuff. And then you know urban planning
Speaker 3: for example, understanding. I remember I interviewed a guy in
Speaker 3: the earliest days of my career who worked for the
Speaker 3: Illinois Department of Transportation, and he told me a couple
Speaker 3: of interesting things. He said, you know, one is, when
Speaker 3: you plan to build new highways, you cannot project out
Speaker 3: the new traffic you'll expect to get based upon this
Speaker 3: new highway. You have to build at least back then
Speaker 3: you had to base it upon current traffic patterns and
Speaker 3: so there's a lot of effort that goes into that.
Speaker 3: And you know, getting back to the data side of things,
Speaker 3: we got about a minute and a half left here.
Speaker 3: All this data is very useful. I mean for like potholes,
Speaker 3: for example, do you guys see that program with Domino's
Speaker 3: Pizza with like call in tol us What a podolism
Speaker 3: will fix it for you? Almost Like that's brilliant.
Speaker 1: Yeah, even though I don't think the cities have the
Speaker 1: problem that they have people sitting around not knowing what
Speaker 1: to do and waiting for somebody calling in for a
Speaker 1: portol But I'd like to jump on on that really
Speaker 1: quick with like a twenty second thing about AI, because
Speaker 1: we haven't really talked about AI. But this is where
Speaker 1: AI starts to shine a lot in our industry because
Speaker 1: we gather so much data and there's different approaches on AIS.
Speaker 1: As the server based AI, which we call a data lake.
Speaker 1: You just dump all that data in there and you
Speaker 1: let the artificial intelligence go through and understand what do
Speaker 1: we learn out of all this data? And then the
Speaker 1: other thing is one what we have not seen yet,
Speaker 1: but we will see soon is what is called h
Speaker 1: ai so Edgai means is ai actively learning in your
Speaker 1: car and it starts to make improvements to the behavior.
Speaker 1: So this is probably a complete different additional segment of
Speaker 1: an hour. So I will not I will stop right here.
Speaker 1: But as you can hear, we can talk about that.
Speaker 4: We can for you that one absolutely well.
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Speaker 15: Majorcis says Americans should not be concerned about a recent
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Speaker 15: This Week that rules have recently been changed allowing drones
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