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