A further benefit of highly automated and autonomous vehicles in future, is the fact that the driver can better utilize the time spent in the vehicle. Initial tests show that the time can be used for entertainment, for example in the form of movies, work, and also resting up. Rupert Stadler, Audi CEO, speaks in this context of about 25 h, which customers can gain through the use of highly automated and autonomous driving [23]. A study by Horvath and partner, which was conducted in cooperation with the Fraunhofer Institute for Industrial Science, showed that the additionally gained time in the vehicle could lead to a billion Euro market [24].
Autonomous driving will make a contribution to increasing social justice. Older citizens, sick and physically challenged people are partially excluded from automobile individual mobility today. They cannot or are not permitted to drive vehicles themselves. Autonomous vehicles enable them to use this form of individual mobility, since a robot is the driver. In a video on user behavior in the case of autonomous vehicles from Google, shows a blind elderly man, as a representative of this group of people, who is quite obviously enjoying the trip [25].
Further benefits are expected from the influence on inner city traffic and city planning, once autonomous vehicles have become reality. Public space can most probably be utilized differently and more advantageously. It can already be seen that automated parking, which will be offered in vehicles in the near future, will improve the usage of parking space in park garages by approximately 30%. New traffic and city development concepts will be possible. In the context of the Audi Urban Future Initiative [26] the city of Somerville, a suburb of Boston, demonstrates what a suburb with autonomous vehicles could look like. It is planned to realize this concept in the near future [27].
The benefits mentioned are difficult to quantify. Nevertheless, there are first attempts. A study by Morgan Stanley estimates the benefits of automated and autonomous vehicles in a pessimistic scenario 0.7, an optimistic scenario 2.2 and in a realistic scenario 1.3 quadrillion USD [11, p. 8]. The 1.3 quadrillion are made up of mainly 488 trillion through savings by avoiding accidents, 507 trillion through productivity gains through better utilization of the time spent in the vehicle, 158 trillion through fuel savings and 138 trillion through the avoidance of traffic jams. A study by the Rand Corporation [28] goes on the assumption that autonomous driving reduces accidents, makes a contribution to social justice, avoids traffic jams, reduces land usage and reduces environmental damage, among others.
39.4 Automated & Autonomous Vehicles and Their Infrastructure
Automated vehicles can be seen as so‐called cyber physical systems, i. e. a combination of physical product and associated computer supported information processing. Cyber physical systems address the close connection of embedded systems for the control and steering of physical processes using sensors and actuators via communications connections with the global digital net (cyberspace). The higher the proportion of information‐ and communication technology, i. e. the degree of automation in the vehicle, the larger and therefore more central will be the proportion of computer supported information processing in adding value and in the development of a vehicle.
Automated and autonomous driving can be described by the structure “Entry – processing – output”, well‐known from information processing. The input of the data, which the vehicle requires for automated driving, occurs via sensors. The sensor technology required for automated driving, is illustrated in Fig. 39.1 as an example on an Audi RS 7 [29]. This vehicle is able to drive automatically at speeds of up to 240 km/h on a closed racetrack. The cars available from other manufacturers currently possess – although there are manufacturer‐specific differences – basically a sensor technology, which is comparable to that of the Audi RS 7. Not every model of car, however, has all of the sensors built into the Audi RS 7.
Fig. 39.1Audi RS 7 piloted driving concept
The sensor technology of the RS 7 consists of GPS, ultrasonic sensors, radar‐ and camera systems. Each of these sensors captures different aspects of the environment on the basis of specific features. Therefore, ultrasonic sensors, for example, are efficient only in the nearby area and are used for parking assistants. Radar systems are effective for greater distances and are used for automatic vehicle interval control (in Audi terminology: ACC Adaptive Cruise Control). Infrared sensors are used predominantly at night. Camera systems capture and identify objects, such as other vehicles, for example, and other motorists or pedestrians and follow these. The GPS system is a further part of the sensor technology, which recognizes the location and movements of a vehicle. Differential GPS is based on the well‐known and commonly used GPS, but it is more precise. The Lidar (Light Detection and Ranging), a sensor technology based on laser technology, which is related to radar technology, will, in future, enhance the sensor technology of automated and autonomous vehicles in the near future and will increase the precision and range of environmental detection. Additionally, the entry of the destination takes place via the user interface of the navigation system. The development of the sensor systems and the software to recognize objects, identify them, track them and, in a best case scenario to predict their behavior is a focus of research and development for automated and autonomous vehicles. In the area of object recognition, identification and tracking, a jump in development is expected through the increased utilization of machine learning, or deep learning [30].
The perceptions of the individual sensors are compiled during processing to show an image of the environment. The processing system knows the destination from the entry into the GPS system and the route to this via the maps. On this basis how the vehicle should move is calculated in real time. Processing of the entries into driving commands is a computing process, which has to take place in real time. It places high demands on the computing process. The processors, which are responsible for this, will in future constitute a central component of vehicles. Individual experts are of the opinion that this central unit will equal the engine in significance for the vehicle. The issuing of the driving commands is effected by so‐called actuators to the electronic accelerator, the electronic brakes and the electronic steering. In the automated vehicle, these power units are addressed via the network, i. e. “by wire” and moved by electric motors. The movement of a vehicle exclusively “by wire” is a jump in development, which is a deep encroachment into the development and operation of vehicles.
The actual process of automated and autonomous driving will be completed by further entry, processing and output functionalities. Above all, the interface to the driver, the so‐called user interface, is of great significance. A central aspect in automated and autonomous vehicles is the process by which the driver wants to, or has to, because of a dangerous situation, return to taking control while the vehicle is travelling in automated mode. Problems, which have to be solved for this process are, for example, how the driver will be informed that he or she needs to take control, or how he or she receives the information that he or she can safely control the vehicle. Already today there are different interfaces to the driver in automated vehicles, for example warning lights, which are projected into the windscreen, acoustic signals or vibration of the steering wheel with or without automatic steering correction if the vehicle begins to leave the designated lane. A further aspect which will play a major role in future is the interface of highly automated and later autonomous vehicles with the environment, for example pedestrians.
When vehicles travel for longer periods of time in highly automated or later autonomous mode, it will be possible to construct and use the interiors of vehicles differently. In this context, one speaks of a change from driver‐orientation to benefit‐orientation. The benefit‐creating usage of time in the vehicle is in the foreground. The steering wheel, for example, is reduced in significance in a
highly automated vehicle. The Mercedes F015, a prototype of an autonomous vehicle, has only a rudimentary steering wheel. Autonomous vehicles will not have a steering wheel anymore. The Mercedes prototype and the Google vehicles illustrate that highly automated and autonomous vehicles enable innovative design of the interior. What these vehicles will eventually look like will be decided by the customer, or how they will imagine spending their time when the vehicle is travelling autonomously.
In future, not only the interior but also the external appearance, or the concept of the vehicle will most probably change [31]. The Google prototypes are built for low speeds and short distances, the so‐called “last‐mile”. Their area of operation is the autonomous short‐distance traffic, for example home from the railway station. Road trains, a type of bus with a capacity of up to 20 people, represent a mixture of classic bus and taxi. They serve the more individual transport of several people over short or medium distances. Contrary to these automatically travelling special vehicles will be the highly automated and later autonomous universal vehicles. They are similar to today’s vehicles, but enable highly automated and autonomous driving.
Independent of the development of automated and autonomous driving, today’s vehicles have already been connected over the last few years, mostly via the mobile network. Currently this interconnectedness is largely used for local communication, for text messages, and for entertainment. The interconnection of vehicles (Car2Car.communication) with the infrastructure (Car2Infrastructure‐communication) and with cloud services will play a large role in highly automated and autonomous driving. Car2car‐communication, for example, will enable the process where cars will transmit information about speed, directional change or danger situations directly to all other vehicles in the vicinity. Car2Infrastructure, for example, connects a vehicle with traffic signs or traffic lights. Of special significance for highly automated and autonomous driving is the interconnection of the vehicle with cloud services. Highly precise maps are of central significance for highly automated and autonomous driving. Through interconnection with, for example, highly precise maps available from the cloud, the steering of the vehicle can be improved in extension with the environmental images received in the vehicle by the sensors. Information about temperature, weather, roadworks or danger situations can be made available to the highly automated and autonomous vehicles. At a price of 2.4 billion euro Audi, BMW and Daimler have bought HERE, the map division of Nokia against this background [32]. The aim is to make available to highly automated and autonomous vehicles digital services, for example in the form of maps or route information, in the sense of a digital ecosystem together with other partners, based on the highly precise map material from HERE [33]. During the CeBIT 2016 in Hannover, Huawei presented a first prototype for 5G networks. This technology will be of great significance when large amounts of data are exchanged between vehicles, with the infrastructure or with cloud services [34, 35].
39.5 Automated & Autonomous Vehicles and Their Infrastructure
Highly automated and later autonomous vehicles will change the automobile industry. In a structure‐changing manner, as we know it from, for example, electronic commerce, we will see the corresponding changes from a market penetration exceeding approximately 10%. The proportion of online purchases expressed as a percentage of total purchases in Germany in 2015 amounted to approximately 11.5% [36]. The repercussions on the retail trade are considerable. It is to be expected that the automobile industry will soon feel the effects of highly automated and autonomous driving and that this will cause structural changes shortly after 2020. These disruptive effects of automated and autonomous driving in the automobile industry will further be exacerbated by additional megatrends: The development towards electric vehicles is a trend change for the established automobile industry, whose consequences are currently not foreseeable. Tesla has proven that many customers in the high price bracket are willing to purchase electric vehicles, regardless of the fact that electric vehicles are afflicted with many uncertainties.
A further megatrend, which can alter the changes in the automobile industry, results from the so‐called “share‐economy”. Enterprises such as, for example, AirBnb or Uber have shown that the so‐called share‐economy was able to shake the lodging and taxi industries in its foundations. The trend of many young people to see themselves as participants of the so‐called share‐economy will have an effect on the mobility sector. Offerings such as Drive‐Now and Moovel by Daimler or Mobility in Switzerland show that the share‐economy is also moving into individual traffic.
The growing environmental consciousness and, concretely, the aim of more and more people to reduce their carbon footprints, increases the speed of the change.
These three megatrends will intensify the structurally changing effects, which occur through the development towards autonomous vehicles.
39.5.1 The Growing Impact of Information Technology
Automated and autonomous vehicles can, as already indicated, be seen as so‐called cyber physical systems. The proportion of information and communication technology to the added‐value and the functionality of the vehicle is a deciding factor in automated and autonomous vehicles. In a study by the Fraunhofer Institute for Industrial Engineering and Organization, which was conducted by mandate of the Federal Ministry for Economy and Energy, it is estimated that the market volume of systems for highly automated driving will grow from 4.38 billion euro in 2014 to 17.3 billion euro in 2020 [37]. The valued percentages in this market are spread as follows: 36% for sensor technology, 19% for control units, 18% for software development, 17% for validation and testing (incl. sales margin) and 10% for user interface, maps and back‐end services as well as systems integration [37].
The automobile industry has to establish expertise in the information and communications technology at the same high level as in the classic competencies, which it built up in over 100 years. Different automobile manufacturers and suppliers, which are affected by precisely these changes, are making great efforts to master this challenge. The absolute figure as well as the relative number of people working on information and communications competencies, above all software development, is rising. Continental, one of the large component suppliers, has already employed more than 10,000 software developers since 2012 [38]. Numerous automobile manufacturers, such as VW, BMW or Daimler and also suppliers such as Bosch or Michelin have established labs in Silicon Valley in order to be closer to the development of information and communication technology. The VW lab is integrated into the campus of Stanford University [39]. Many prototypes of automated and autonomous vehicles were developed in this laboratory in cooperation with the Engineering Department of Stanford University. General Motors works together with Carnegie Mellon University, one of the other hot spots of automated and autonomous driving [40]. Toyota invests a billion dollars in machine learning in universities on the west and east coats of the USA [41]. All of these efforts indicate that the traditional automobile industry and its suppliers have started with the so‐called digital transformation. This transformation process is proving to be very difficult when talking to leading personalities from the automobile industry. The further development of vehicles to cyber physical systems is not undisputed with many experienced employees of the automobile industry. The cultural change of companies, which, in the past, produced mechanical products with a few electronics, to move to products for which, in future, software is the deciding component and the metrics of Silicon Valley apply, is a difficult step for traditionally thinking and classically trained engineers. A further reason for resistance is the development from driver to benefit orientation, which is being initiated by autonomous driving. For many traditionally thinking proponents of the automobile industry it is simply not feasible that, in fu
ture, not the sporting driver, but a programmed robot has control over the vehicle. The change in the sector is visible: In his speech at the Consumer Electronics Show 2014, Rupert Stadler made clear that digitalization in the automobile industry has top priority [42]. Numerous CEO’s of the automobile industry have followed his example. Today the CES is not only one of the most important fairs for consumer electronics, but also one of the most important automobile fairs.
39.5.2 New Competitors & New Suppliers
The digital transformation of the automobile industry opens, just like every technological change, chances for new suppliers. Above all, the combination of electro‐mobility and digitalization motivates people from outside of the industry and start‐ups to invest in mobility. Tesla is a well‐known example, Faraday [43] is a further automobile manufacturer, which is developing in Silicon Valley. Mobileye, an Israeli high‐tech company, which develops camera systems and the corresponding software, among others, delivers central components for automatic and autonomous driving to many traditional automobile manufacturers.
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