The push towards automated and autonomous driving is not being driven by carmakers. Mobility service providers, fleet operators, cities, and delivery businesses are significantly more enthusiastic about this technology.
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A paradigm shift in transportation
How can an industry tell whether it’s going through a disruptive change? One of the most distinguishing features of such a shift is that technology innovation is no longer driven by the traditional industry leaders, but by new companies.
Another evident feature of disruptive change is that it affects not just goods and technology, but also customer structures and business models — in other words, all of the traditional business coordinates.
The smartphone is a typical example that everyone is acquainted with. It was first released to the market years ago, although not by Nokia, the once-dominant mobile phone manufacturer. Apple, in fact, re-invented the mobile phone as an internet-capable application platform, that today is known as the smartphone, by using its software skills.
In the automobile business, we are now undergoing a major transformation. Two technological developments are driving it.
The first is the concept of electromobility. The all-electric drive decreases the complexity of the vehicle’s drive system and allows new suppliers to enter the market. For many years, we’ve seen this in China, where new automotive manufacturers have focused only on making electric vehicles in sufficient numbers.
The relevance of the battery-charging infrastructure required for electromobility, on the other hand, necessitates a thorough grasp of networked mobility.
Autonomous driving is the second and most significant contemporary technological development. It is projected to lead to new types of cars and business models, owing in part to the advanced driver assistance systems (ADAS) created by automotive manufacturers. Over time, they will have less and less to do with manufacturers’ core business. This, in turn, will have an impact on technical demands.
A complete shift in infrastructure and demands
A self-driving automobile known as a people and freight mover, which will be utilized for both passenger and package delivery services, is one notable example that may soon be visible on the roads.
Many individuals wonder whether developing and producing such people and freight movers doesn’t demand present automotive manufacturers’ competencies and distinctive selling propositions, particularly peak driving dynamics and engine performance. No, such peak values are not required for cars traveling at a maximum speed of 70 km/h.
What about mass-production know-how from the industrial revolution? When it comes to small-batch manufacturing, it isn’t absolutely required. The integration of data, including routing data from delivery services and application-supported data from the mobility provider and its clients, is a critical aspect in the deployment of such fully automated and self-driving cars.
The latter will be crucial for a second key autonomous vehicle category, namely ride-hailing, which is provided by businesses like Uber and allows for the booking and payment of individual journeys.
Mobility ideas such as “Mobility-as-a-Service” or “Transport-as-a-Service” (MaaS and TaaS) are the fundamental drivers behind autonomous driving. Cities and city planners, in turn, are driving these notions and they were players and client groups that the automotive industry has mostly ignored until recently.
Berylls conducted a well-regarded research to determine the influence of robotaxis on the city of Munich. According to the findings, about 200,000 privately owned automobiles might be replaced by a fleet of 18,000 self-driving taxis.
The reason for this is because, unlike passenger automobiles in today’s private transportation, such robotaxis are always on the road, ready to provide passenger transportation at any moment. Privately owned automobiles are only utilized around 5% of the time throughout the day, and the rest of the time they just take up parking places.
As a result, if Munich’s private transportation relied more heavily on robotaxis, 2.9 million square meters of parking space would be freed up for other use.
Autonomous driving companies and technologies are evolving at an incredible pace
This is the type of possibility that comes with self-driving cars. As a result, market categories are already moving or increasing considerably.
According to market analyses based on estimates from Goldman Sachs, Roland Berger, and McKinsey, among others, the autonomous driving market in 2030 could be worth between $12 and $18 billion for passenger cars (including hardware, software, services, and possible upgrades) and up to $36 billion for commercial vehicles. Every year.
The market for people and freight movers, on the other hand, far outnumbers these estimates. Analysts estimate that this industry has a potential worth of $20 to $50 billion each year, with the freight movers taking the lion’s share.
And, assuming that the correct legislation is approved soon, such as allowing vehicles without drivers to travel on public roads, ride-hailing is predicted to outperform the passenger car industry by a factor of two, with a market potential of $18 to $35 billion.
In the typical passenger automobile category, automated driving features are “add-ons” based on today’s sophisticated driver aid functions employed by consumers and car purchasers. They also result in improved safety ratings, such as the EuroNCAP.
Autonomous driving for people and freight movers, as well as vehicles for ride-hailing, is, on the other hand, a need for the realization of wholly new kinds of mobility for various client categories. Other automobile-related needs may be “narrowed down” as a result.
This will have a significant influence on the vehicle’s design and technical foundation, as well as its expenses. These automobiles no longer fall into the small, mid-size, or premium passenger car categories that we previously assumed. This is particularly true for people and freight transport, which will rely on “purpose-built vehicles (PBV).”
They will not only have a diverse appearance and technical foundation, but their supply chain will also change throughout the production process.
Because vehicle technology is becoming less complicated, system providers such as ZF can now supply the whole mobile chassis platform, including electric drive, brakes, and steering, sensors and control software, as well as integrated safety in the case of passenger transport.
Depending on whether the vehicle will be utilized for passenger transport or delivery, specialist suppliers might be hired for vehicle bodywork.
The most important thing is to get to your destination safely and on-time
What’s the difference between a self-driving vehicle transporting a passenger or freight from point A to point B? There are a lot of similarities if you look at the work only from the perspective of driving. That is also why the people and freight moving sector has so much promise.
After all, in order to satisfy transportation growth expectations, the logistics sector needs innovative solutions based on autonomous driving, particularly given the dwindling number of competent drivers. Self-driving trucks on a hub-to-hub route are another possibility.
Starting with distribution hubs near to town, items might be transported into the city in an automated and all-electric manner. As a result, deliveries in the city center may be made at any time of day or night. This kind of service will eventually become essential in distributing commodities to cities with populations in the millions.
Furthermore, the trend toward increasingly urgent last-mile deliveries, which was observed in ZF’s 2016 Future Study and has remained since then, necessitates innovative transportation solutions. This isn’t simply wishful thinking anymore. Kroger, a U.S. grocery chain, and Nuro, a start-up and PBV maker, formed a cooperative collaboration in 2018.
Customers near a Kroger store in Scottsdale, Arizona, may get same-day food delivery utilizing the autonomous cargo mover from Nuro. Kroger is still the biggest supermarket chain and the third-largest retailer in the United States. This is an experimental strategy for Kroger to extend its online business, which, if successful, would swiftly move to other areas in the United States.
Success in this new market requires serious computing resources
Even in the case of ride-hailing, the market potential and predictions are outstanding. According to Goldman Sachs analysts, the market will be worth $285 billion in 2030. Suppliers may successfully harness this potential, particularly if self-driving cars are deployed, which have no running expenses.
As a result, ride-hailing service Uber has, at one point, heavily invested in driverless vehicles. For example, it signed a $500 million cooperative relationship with Toyota. Waymo is a young but financially formidable business that is gearing up to become a market leader in autonomous driving.
This spin-off from Google’s previous self-driving vehicle project has already completed a significant amount of test kilometers. The fleet makes advantage of Waymo’s fundamental competence in seamlessly linking sensor technologies (radar, LIDAR, camera), software, and AI algorithms – all without building its own cars.
The Silicon Valley firm relies on collaboration with Jaguar and Fiat Chrysler for its cars, which are still considered test fleet. Waymo will undoubtedly play a key role in the emerging market for AI-controlled robotaxis.
The self-driving shuttle is basically a data platform for such new transportation providers. This is where the sensor data is evaluated and trajectories are determined. For Mobility-as-a-Service and Transport-as-a-Service applications, the data from the mobility or delivery client must also be incorporated.
This necessitates a tremendous amount of computational capacity in the car, which is presently unavailable from traditional vehicle electronics. Furthermore, the data platform must be open in general in order to incorporate the customers’ routing software.
The ZF ProAI, a powerful central computer that combines automotive control functions, AI software for autonomous driving, and the user’s MaaS or TaaS-related data, is an appealing option for this expanding industry. In a nutshell, it’s an automotive-grade supercomputer that’s also freely expandable and open to any technology.
The conclusion? The future looks “automatic”
Future transportation will be much more pleasant, personalized, sustainable, and, above all, efficient than urban mobility in the early twenty-first century. New mobility ideas, such as autonomous ride-hailing, will fulfill the bulk of mobility demands, especially in cities, which are the primary drivers of autonomous driving development.
The “modal split,” or moving between several modes of transportation, is expected to usher in a new age of urban mobility. The mobility of the future will alter quickly in certain locations. With a strategic emphasis on “Next Generation Mobility,” we document not just prior types of private transportation and passenger and freight transportation, but also emerging forms of mobility.
ZF’s complete spectrum of knowledge, which includes autonomous driving, electric mobility, integrated safety, Vehicle Motion Control, and digital competence, is also appealing to “new mobility customers” in the process of acquiring a presence in the market.
Those who can see future trends early on, predict solutions, and grab chances to profit from the automotive industry’s disruptive upheaval will be the most successful.