In the coming years, mobility solutions—or how we get from point A to point B—will bridge the gap between ground and air transportation—yes, that means flying cars. Technological advancements are transforming mobility for people and, leading to unprecedented change. Nand Kochhar, vice president of automotive and transportation for Siemens Software says this transformation extends beyond transportation to society in general.

“The future of mobility is going to be multimodal to meet consumer demands, to offer a holistic experience in a frictionless way, which offers comfort, convenience, and safety to the end consumer.” Thinking about transportation differently is part of a bigger trend, Kochhar notes: “Look at few other trends like sustainability and emissions, which are not just a challenge for the automotive industry but to society as a whole.”

The advances in technology will have benefits beyond shipping and commute improvements—these technological advancements, Kochhar argues, are poised to drive an infrastructure paradigm shift that will bring newfound autonomy to those who, today, aren’t able to get around by themselves.

Kochhar explains, “Just imagine people in our own families who are in that stage where they're not able to drive today. Now, you're able to provide them freedom.”

Show notes and references

• SAE levels of autonomous driving
• Digitalization for the Automotive & Transportation Industry

Transcript

Laurel Ruma: From Technology Review, I'm Laurel Ruma, and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace. Our topic today is the future of mobility.

In 2011, Marc Andreessen famously said, "Software is eating the world." Now, 10 years later, we're examining how software is eating the car.

Consider this: today's cars have more software in them than mechanical parts. Autonomous vehicles are just one part of the story; the other is the rapid progression of artificial intelligence and how vehicles are being built. Two words for you: engineering, innovation.

My guest is Nand Kochhar, vice president of automotive and transportation for Siemens Software. He joined Siemens in 2020, after almost 30 years at Ford Motor Company, where he held a number of positions, including Global Safety Systems chief engineer and executive technical leader. This episode of Business Lab is produced in association with Siemens.

Welcome, Nand.

Nand Kochhar: Thank you, Laurel. It's good to join you.

Laurel: What does the future of mobility look like to you?

Nand: When you look at the automotive industry, it's going through an unprecedented transformation. It feels like it's setting itself for the next 100 years because the industry has been fairly stable in terms of technology innovations and has been progressing in a continuous improvement mode. Today it is going through a major shift. When we look at trends like the growth of the world population, that drives trends like urbanization, mega city concepts. With those trends, cities are getting crowded, and that poses a huge challenge for mobility solutions for people living in cities all over the globe.

The future of mobility is going to be multimodal to meet consumer demands, to offer a holistic experience in a frictionless way, which offers comfort, convenience, and safety to the end consumer. Look at few other trends like sustainability and emissions, which are not just a challenge for the automotive industry but to society as a whole. To support sustainability and the consumer trends we just touched on, the future of mobility looks to be connected, autonomous, have a shared mobility, and be electrified—in other words, CASE as an acronym.

Future mobility solutions are crossing the boundaries of ground and air transportation with solutions like flying cars, vertical take-off and landing units (VTOLs), and drones for transporting goods. You can see how the future of mobility of both people and goods is transforming, and that's what I meant by the unprecedented change we are going through. Now we can talk about all aspects of CASE, which we just defined—let's start with electrification.

You see in the news that some governments around the world are banning the sale of internal combustion engine (ICE) vehicles by 2030. Then, you see huge investments by public and private sectors on electrified production systems. It is projected that 50% of automotive production will be electrified by 2030. It implies that while internal combustion engines will be around, there's going to be a mix of hybrid, plug-in hybrids, and pure battery electric vehicles coming into the market. You can see how the trends are transforming and how the mobility space is changing as a result of these trends.

Now, when we look at electrification, battery technologies continue to mature, and innovation is at the forefront. In fact, you could say innovation is at the highest level in my 30-plus years working in the automotive world. When you consider battery electric vehicles, obviously we started from lead acid batteries. In the Gen1 electric vehicles, we moved to lithium iron-based batteries, and we’re now moving into solid-state batteries and some other new innovations, which we are not even talking about.

As these innovations in battery technologies mature, some of the concerns of the early days of electric vehicles—for example, the range anxiety, the long battery charging times — those types of concerns are slowly going away. Now with investments in charging infrastructures and the ability to charge in less than 15 minutes, that is raising consumer acceptance at a heightened level. So, one of the trends on electrification is not even a trend: it's becoming more real. We can pick any country around the globe. There's huge investment. In the west part of the US, the infrastructure is already built in place from a charging standpoint. People are driving from city to city, let's say LA to San Francisco, and are getting more comfortable every year driving electrified vehicles.

Looking at another trend—everyone wants to be connected. They want to continue from home into their next home, which is their vehicle, or any transportation system. What they want is to make sure that whatever they're watching, if they're watching a Netflix movie in the house, they want to continue watching while they sit in the car. That is the level of connectivity demand from a consumer standpoint, because everyone is carrying an edge device. It could be a phone, or a computer, and everything is connected—even in the vehicle—as well as it is in the house. So, you can see a major trend from a connected standpoint.

Laurel: I think that's particularly helpful to set the stage that we're not just talking about what we think of as the traditional car. And just for our listeners, CASE is an acronym: connected cars, autonomous or automated driving, shared, and electric.

When we think about the auto industry, even though we are thinking about all the aspects of mobility, that shared aspect plays a big role, doesn't it? Because, as you mentioned, it could be an electric car, it could be a drone, or it could be a different vehicle—especially when we're thinking about industrial applications like delivery vehicles, for example. So, when we think about the mobility of the future, are you also deconstructing what a vehicle means?

Nand: Laurel, you touched on the point. When we talk about mobility, it's not just about about cars or trucks or SUVs anymore— everything is well-connected. And what I said in the opening, one of the trends is multimodal mobility. So, when going from point A to point B, there are several modes of transportation, and consumers over the next decade or so are going to be using more and more of those multimodal modes. It could be taking a train up to a certain point, and then using an electric bicycle. It could be sharing a taxi after that point to get to the ultimate destination. All these things are driving a major shift in transportation, and also a major shift in the business models getting generated. It's redefining the entire industry and its ecosystem.

When we talk about ecosystem, it covers not only the cars and trucks and the traditional way of looking at things, it is also redefining the Uber and Lyft business models, for example—those are the shared mobility operations all over the globe.

Laurel: When we do think about cars or vehicles, specifically, it's easy to center our orientation of what the future looks like with the autonomous car. We're not quite there yet. The fifth level of autonomous driving is total viability and full automation. What stage are we at now, and what can we look forward to the next year or two?

Nand: If you look at the Society of Automotive Engineers, (SAE) definitions of levels, Level 1 and Level 2 are partial automation. We are already there with a majority of the large-scale original equipment manufacturers (OEMs) providing their products. That is, you have automation in terms of the steering, or in the braking. Good examples could be advanced driver-assistance systems (ADAS) features like adaptive cruise control or autonomous emergency braking. Those things are happening, and they have been maturing over the last few years. The next level is Level 3—that's where it gets a little murky. Some OEMs are claiming they're already at Level 3. Others are cautious about that from a safety standard standpoint. At Level 3, the system will warn you, and then the user has to take over in case of an emergency or if the system is not responding well.

Some companies are claiming we are already at Level 3, and that's in that stage of migration where it depends on what country and what company you’re talking about. But you could say from a technology standpoint, we are at Level. Then we come to Level 4. Level 4 is where you have to define a design domain, but everything else is working autonomously—so you add some constraints. We have several pilots projects around the world at Level 4. From a technology standpoint, you could say we have Level 4 running on public roads. I'll use examples in the U.S. In Phoenix, Waymo has pilot programs for shared rides, and recently they announced they're going to be doing similar things in San Francisco. In another example, the Siemens Mobility group has been working with Bahn Hamburg in Germany, and there's been a lot of collaborations for shared ride pilots that would be considered at Level 4.

So, from a technology standpoint, you could say we are at Level 4 running in the environment as well. Now, of course, the reason it's not a mass deployment is because you have to take into consideration all the other things like public policies and safety standards. For example, in the US, the National Highway Traffic Safety Administration (NHTSA) declares what is safe and what those standards are. As things mature, you'll see that Level 4 will become more and more dominant. Level 4 autonomy has been achieved not only in cars and trucks on public roads, but also in the trucking industry. Level 5, as you said, is a bit further away. That's where you need even more fail-safe technologies. Again, companies are continuing to make progress on that, but that's where we are in the levels of autonomy today.

Laurel: Could you share some examples of how autonomous vehicles—not just cars—will be integrated into our lives in the next few years? What does that look like as you leave your house to go to work?

Nand: That's a very good question. We’re starting to see with the two examples in Phoenix and San Francisco how these vehicles are getting integrated into our lives, as well as with the Siemens Mobility, the shuttle I mentioned in Hamburg. So, you can already imagine in a given city, the shuttle is being run autonomously. I think there's a pilot program at the University of Colorado. So, within using the school system as a boundary, there are autonomous shuttles running. If you take that a little further, when these things mature, we’ll be running robo-taxis. In other words, you don't have a driver, a human driver or a safety driver, behind these cars— they are being operated as a fleet. So, the business models for companies like Uber and Lyft, or whoever else they collaborate with, that's going to change and redefine itself. So, that's a huge shift.

On personal front, I would say people will become comfortable dropping their kids at a soccer game or at school using robo-taxis, so it's going to become integrated in our lives. What I really get excited about is, as the aging population gets restrictions on driving, or driving conditions or driving late at night, or people who are not able to drive today, this level of autonomy offers a total freedom. On the human side, that gets me excited and keeps me going on working on technologies, because it's freedom to travel for all.

In a way, I could say it redefines Henry Ford's original vision of providing affordable transportation to everyone, which the company advertised back in 1925—to open the highways to mankind. Level 4 autonomy will open the highways to mankind in a totally different way—it will offer total freedom, and that's a huge change and a mega shift from where we are today.

Laurel: I love that idea, the autonomous vehicle providing autonomy to folks who don't have it currently. That is really a massive societal shift.

Nand: Just imagine people in our own families who are in that stage where they're not able to drive today. Now, you're able to provide them freedom. It takes the burden off you to go pick up someone or drop them off, because you're confident these technologies are going to work. So, that's the societal trend we are talking about.

Laurel: Isn't that interesting, because here we are innovating with how vehicles are being developed, and decades ago, Toyota developed the Toyota Way philosophy, which is the iterative process that became crucial to the industry and allowed for rethinking and remodeling at different times during the development of the vehicle. How do you think about product development now in 2021?

Nand: One of the things you touched on in the opening was about how software is eating the world. We have a similar saying: software is eating the car. So, when you talk about software, one word comes to mind from a product development prospective: agile product development. So, agile methodologies have been used in the software world quite extensively for past few years. The same methodologies are now migrating into agile requirement's management, into agile product development requirements and changing the concepts of design into generative design, as an example. So, it's not just the software. Software on its own can't deliver the promises we are talking about, autonomous, and electrification, and shared mobility, etc. It has to work hand-in-hand with the corresponding hardware, and that hardware is becoming more electronic—in the vehicle itself and outside of the vehicle.

Let's go even further into hardware and software working together. You have a lot of embedded software in the vehicle, and that embedded software is also connected to the rest of the infrastructure. So, that's what we mean when we talk about vehicle-to-vehicle infrastructure, or vehicle to infrastructure of the city traffic system or the lighting system, as an example. So, cars are becoming computers on wheels. And now, one thing comes to mind when you're going through a major shift like that: you need a new electrical architecture, you need a new vehicle architecture, and these things have to work hand-in-hand with the software. So, what happens as a result is that complexity goes through the roof. The automotive business is complex to begin with, but now with this shift happening, complexity is raised to an enormous level. And that's where I think we come into play from a digitalization perspective, that we want to convert complexity into a competitive advantage by offering solutions for digitalization for the automotive industry and its ecosystem.

Laurel: How is product development accelerated with simulation? Because that is something you need to have when you talk about that added complexity, especially when you're starting to integrate artificial intelligence, right?

Nand: I'm glad you brought up simulation, it’s one of the areas I've been really passionate about for the last 30-plus years. Simulation has become the only way, in my mind, to solve the problems of today and to get the industry ready for tomorrow. The reason I say that is, in the example of autonomous vehicles, if you have to prove an autonomous vehicle works safely, you'll have to drive billions of miles in a physical test environment. Obviously, that's not possible. That will take an enormous number of years.

So, simulation becomes critical in solving what we call edge cases, what the autonomous vehicles are going to go through, so that you minimize the number of physical tests you will have to run. The majority of the development of autonomous vehicles and the sign off you can do in a simulation environment. That's an extreme example of how simulation is becoming the heart of future product development, not only in the product development, but also in manufacturing and in the service piece of it.

Then you go even further. Within product development design simulation, and the testing aspects of it, simulation again becomes very important. The test and the simulation have to correlate so the engineers can build their confidence in ultimately signing off on their vehicles, or any product for that matter. So, you see simulation and software becoming a central piece of product development—and, in my mind, maybe a strong statement, but the only way to go forward. Any company that is not into simulations will be left behind, in my perspective.

Laurel: How does artificial intelligence play into the simulation part of it as well as the entire product life cycle? Because now there's no literal drawing board to go back to. If you need to make a change, you tweak it within the simulation and the generative design then follows, correct? Or vice versa. But you're constantly making those slight adjustments, and then you can just test it again in real time?

Nand: That's right. Artificial intelligence, others also call it machine learning, plays an important role in our accelerated product development way of doing things. Industry always has challenges to deliver, at the end of the day, quality, cost and timing. You need to deliver these things to sustain business today and in the future while you're continuing to innovate, while you bring in new technologies, new vehicle types, etc.

When you look at the end-to-end process—what we call a digital thread, a closed-loop process from end-to-end, from concept, to design, to manufacturing, to service in a closed-loop manner—I think artificial intelligence plays a big role to improve the quality on an ongoing basis and to provide real-time feedback to improve either on the performance or on the quality aspects, or to optimize for cost.

We can chunk this out into several pieces because AI and machine learning, and in some places even IoT, go hand in hand. Let's use a manufacturing example. In today's modern factory, the factory is equipped with many sensors which are generating data, even at a machine level or at an assembly level. That data needs to be sent somewhere. In our case, we feed it to the cloud, where the information is processed and results are sent back to inform decisions for the next part coming off the line or next car coming off the line as a quality improvement, in this example.

So, you see AI or machine learning is playing an important role in all three aspects: design, manufacturing and service.

Laurel: How can AI or machine learning be used with the data that's collected from autonomous vehicles to create safer vehicles? Now that we're out of the lab and into the streets, what kind of real-time feedback do you think is going to be possible?

Nand: Some of this is already being done today. For pioneers in the technologies, in companies like Tesla, for example, they're running what's called the “ghost mode”—that is, vehicles are running on the road to collect data. Obviously, they've got vision systems or perception through the cameras, radar, and they've also got many sensors on the vehicle itself. That data is being collected in normal driving conditions. And in case there is an incident, that data gives you an entire picture of what was going on, what speed things were running, what were the surrounding vehicles, what were the weather conditions, and so forth.

So, that data is being fed live, or sent back to the design communities, and that's how you can learn what algorithms need to be tweaked, how we need to modify those based on that information. So, there's a continuous improvement in the algorithms and the decision-making through those algorithms, which is all based on AI.

Laurel: What lessons can industries outside automotive learn from innovations in vehicles and mobility?

Nand: There are a lot of lessons. Across industries, there’s a lot in common, especially in the manufacturing arena, whether you take an aerospace, an automotive or even a space industry—you can even look at industrial machinery, heavy equipment, or consumer product companies. The first common fundamental is around the technology. A lot of times, we end up using the same or similar technologies, and they form the basis. Tto be honest, even for automotive, we take learnings from farm equipment, as an example, or heavy equipment industries, because some of those are in a constrained environment, and autonomy and electrification is in those industries equally prevalent.

There are other areas of basics, let's say materials engineering. That is common. So lightweighting is always a huge pressure on the automotive industry because in electric vehicles, you want to increase the range; in internal combustion engines, you want to increase the fuel economy. And for that, lightweighting is one of the big factors, whether it's composite materials or whether it's any other exotic material. Aerospace has the same challenge—they want to make the planes lighter.

We talked about the software. Again, software in the electronics and semiconductor industry, it is predominant.  They’ve been using it for years, and they are in leadership positions from a technology perspective. Today's modern car, and the future car, is heavily dependent on semiconductors and chips, and you can see the learnings can come from that industry into automotive—one of the unique things about automotive is that it's the most complex from a mass production standpoint. It's a very complex business, managing the entire supply chain.

Our supply chains have been global for many years, and they're going to continue to be global. Lesson from managing all those supply chains can be applied across other industries. There's a lot of applications from basic materials research that can be applied to electronics and semiconductors, from software, mass production techniques, supply chains—all these lessons learned can go back and forth across industries.

Laurel: Yeah, that is really interesting, especially when we think about this major shift in the automotive industry, and the vehicle and mobility industry, and how that will trickle down through everyone else as well.

Nand: I touched on the technology itself. When it comes to processes, whether it's digitalization or what we call model-based systems engineering, that approach is, again, applicable across industries. It's not just for automotive. It can apply to many industries.

Laurel: What do you see for the future of the mobility industry in  five to 15 years down the line? What do you think we can expect in the consumer market and within the industry itself?

Nand: That’s a very good question. I'll touch on the acronym CASE that you expanded on: connected, autonomous, shared mobility, and electrification. Those trends are no longer going to be trends in 15 years. We going to be living through those. Those are going to be realities in my mind, in five to 15 years. We can chunk this out even further, let's say in a shorter timeframe; in five years, the electrification we touched on is going to be very mature. By 2030, as I said, 50% of the automotive production is going to be electrified. For 2030, to hit that number of 50%, that means products need to be out there.

We already see that. Every major OEM has billions of dollars now invested, and have made announcements about how many electrified products they're bringing on the road. Every year, that number continues to grow, especially when you take a look at that globally. It's not a trend just in the developed nations, in the Western part of the world or in Europe. In countries like China, that trend is at an even faster pace on electrification, as an example.

The consumer today demands to be connected. They are connected through their devices. They're going to expect the same not only in their home, in their hands, in the cell phones, but also in the cars. Autonomous, because it's connected, it is going to offer a level of autonomy because vehicles will be connected to the infrastructure. Vehicles will be connected to the other vehicles on the road. So, the connectedness trend is going to continue to grow.

Autonomy is an interesting one. As I said, we are already at a Level 2 for sure, by a majority of the industry providers, Level 3 by some, and you're going to see in five to 10 years, the Level 4 maturing to a shape that some of the things we touched on in terms of robo-taxis are going to be real. In a 15-year timeframe, you could be looking at the ability to drive under even a Level 5 type of condition.

So, I clearly see all of those trends coming into fruition, and they create new business models. They allow a lot of technology companies to enter the traditional OEMs and guess what: the traditional OEMs then have to continue to innovate because they not only have to compete and offer products in the electrified and autonomous range, but they also have to continue to have their current business, which is the internal combustion engines. They'll be going hand in hand. So, current OEMs have an even a bigger challenge than startup companies or the companies that are working only on electrified or only on autonomous. They don't have the legacy stuff coming with that. We’ll see all these things, and we'll have policies, and we'll have government standards. All those, hopefully, will be shaping to a point that these things will become real in a five to 15-year timeframe.

Laurel: So many possibilities. I can't wait to take a robo-taxi. Thank you very much, Nand, for this fantastic conversation on the Business Lab.

Nand: Thank you, Laurel. I really appreciate it. It's an honor to be talking to you.

Laurel: That was Nand Kochhar, vice president of Automotive and Transportation for Siemens Software, whom I spoke with from Cambridge, Massachusetts, the home of MIT and MIT Technology Review, overlooking the Charles River. That's it for this episode of Business Lab. I'm your host, Laurel Ruma. I'm the director of Insights, the custom publishing division of MIT Technology Review. We were founded in 1899, at the Massachusetts Institute of Technology, and you can find us in print, on the web, and at events each year around the world. For more information about us and the show, please check out our website, at technologyreview.com. This show is available wherever you get your podcasts. If you enjoyed this episode, we hope you'll take a moment to rate and review us. Business Lab is a production of MIT Technology Review. This episode was produced by Collective Next. Thanks for listening.

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