Autonomous ecosystem

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SVG Title Demo example Digital mobility frameworks Two main competitors are racing to enter the digital mobility market. One is a relatively old set of technology and standards called Dedicated Short Range Communications (DSRC) which has been in development for 20 years and has market-ready solutions. The other, newer one is Cellular Vehicle-to-Everything (C-V2X), backed by global tech & OEM market players. The main differences between the two frameworks are: - DSRC’s usability is very limited, C-V2X has a broad range of usability - DSRC’s versatility is fixed – only available via WLAN, whereas C-V2X is explicitly versatile – cellular based - DSRC’s data transfer capacity is relatively low, while projected 5G compatibility for C-V2X forecasts 10x higher capacity than 4G - DSRC’S single signal transfer speed is lower than 50ms (compared to C-V2X at 100ms), which cannot meet collision avoidance requirements - DSRC’s range is set at 300 m, whereas C-V2X’s cellular basis provides no limits of range - DSRC is considered secure, as it cannot be hacked remotely, while C-V2X is accessible remotely These two competing frameworks don’t provide an either / or solution, but rather a combination of the streams. Penetration on the other hand is critical, because the more connected vehicles and objects there are, the more enhanced the system is. 5G – The cornerstone of autonomous ecosystems 5G networks will perform on a new level: - 1-10 Gb/s data transfer speed - Serving 1 million devices per square kilometer at a time - 1 millisecond end-to-end delay time - Near 100% coverage - 99.999% availability - 90% less energy consumption 5G’s main role is connecting things (Iot) and serving industrial clients (industry 4.0). Disruption of mobility is one of the key areas of this new technology, as 5G could provide the infrastructural base for autonomous ecosystems connecting vehicles and ensuring safe transportation. Connected vehicles communicate via sensors and the internet enabling them to see and hear other objects and possibly talk to each other. As a result of connecting vehicles into a network, a central flow control mechanism could be used. In contrast to conventional vehicles, the operation of connected vehicles requires more than one industry to work together. Not only automotive but telco stakeholders, as the providers of key infrastructure, will play an important role in creating autonomous ecosystems. Cloud: Cloud solutions are an important part of the autonomous ecosystem, providing a resilient and high-performance foundation on which to collect, manage, and analyze sensor data. Processing can happen remotely in the cloud. A scalable, highly-resilient cloud-based infrastructure is critical for handling this type of large-scale data processing, while cloud-based data management systems also take charge of aggregating and analyzing real-time telemetric data – vehicle speed and surrounding car proximity – to initiate actions such as braking or switching lanes. Cloud-based networking and connectivity is another important part of the mix. Autonomous vehicles will be outfitted with onboard systems to support machine-to-machine communications, allowing them to learn from other vehicles on the road to make adjustments that account for weather changes and shifting road conditions. Scalability of cloud computing infrastructure along with intelligent data management and transmission capabilities are indispensable for ensuring that all the information is processed properly and securely. This is especially true for destination and address data, which could be considered personal information. Sensors: The autonomous vehicle sensing process tries to duplicate human senses, primarily human vision, and improves on it through multiple sensors, whereas perception involves understanding the 3-dimensional environment using sensor data. The perception process identifies objects, road features and conditions. The prediction process tracks objects and predicts their possible next actions. Camera-based/radar-based/lidar-based sensor systems work together. Multiple sensors and cameras not only identify the location, but also create an accurate 3D model of the surroundings. Visual data (e.g. traffic signs) allow updating of map services in real time. Sensors monitor performance and erosion of all vehicle components, and driving patterns. Predictive analytical models can help forecast part failures on individual cars. Analyzing sensor data from crashes or hard braking will improve safety systems and prevent accidents. Artificial Intelligence Artificial intelligence (AI) is an umbrella term for “smart” technologies that are aware of and can learn from their environments, enabling them to subsequently take autonomous action. Robotic process automation, machine learning, natural language processing, and neural networks all incorporate AI into their operations. What separates AI from general-purpose software is that it enable machines to respond autonomously to signals from the external world—signals that programmers do not directly control and therefore cannot always anticipate. In the autonomous ecosystem, AI is a collective term for computer systems in which the vehicle can sense their environment, think, learn, and take action and is capable of autonomous driving. Forms of AI in use today include, among others, digital driving assistants and robotaxi services. AI works in four ways: • Automated intelligence: Automation of manual/cognitive and routine/non-routine tasks • Assisted intelligence: Helping people to perform tasks faster and better • Augmented intelligence: Helping people to make better decisions • Autonomous intelligence: Automating decision-making processes without human intervention Cyber security As companies pivot toward a digital business model, exponentially more data is generated and shared among organizations, partners and customers. This digital information has become the lifeblood of the interconnected business ecosystem and is increasingly valuable to organizations—and to skilled threat actors. Business digitization has also exposed companies to new digital vulnerabilities, making effective cybersecurity and privacy more important than ever. PwC incorporates four key elements to help you take a broader view of cybersecurity and privacy as both protectors and enablers of the business. Big data analytics Big data analytics is a complex process of examining large and varied data sets -- or big data -- to uncover information including hidden patterns, unknown correlations, market trends and customer preferences that can help organizations make informed business decisions. From the point of view of the autonomous ecosystem, large amounts of data collected by the sensors and generated by the monitoring of the user are the main value. The services industry is looking at “big data” as a way to drive profitable growth. Analytics is used for three types of decisions: 1. direct-to-customer processes, 2. go-to-market processes, and 3. rewriting the profit equation for the entire business system Liability With the emergence of autonomous vehicles in our world, the auto insurance industry, a $700 billion global market, needs to adjust its long-standing risk assumptions — things like accidents-per-vehicle-mile-traveled or human versus mechanical error. The insurance market will see sweeping structural changes as premiums shift from insurers to manufacturers. Insurance may soon be sold in solutions with the vehicle itself. Autonomous technology adoption should reduce the rate of accidents and put downward pressure on premiums. But premiums won’t go to zero. This new technology will not eliminate accidents altogether, and there will still be a need for insurance. Still, the insurance industry’s response largely will be shaped by the fault determination in early cases. Even if statistics demonstrate that autonomous driving is safer, it is not clear where or how the industry, the courts and regulators will look to assign fault. Personal auto policies also need to evolve to match the autonomous driving features chosen by consumers, not to mention address the potential for cyber risk. The automotive industry as a whole, and the auto insurance business specifically, is on the verge of a makeover, and business models are adjusting based on autonomous vehicle technology. Positioning properly to avoid pending pricing pressures and capitalizing on nascent demand and new revenue streams is critical. Privacy The autonomous ecosystem raises key issues in terms of data protection and cyber security. The development and use of connected and autonomous vehicles will involve the collection of a wide range of personal data, including driver details, location, direction of travel, journey history, and average speed and mileage. The connecting of vehicles with infrastructure increases the risk of hacking, just because there are many more entry points for hackers to exploit. It will also increase the risk that a coding bug could cause widespread damage, because an issue in one car could involve accidents with other cars that are communicating with that vehicle. Implementing appropriate data protection compliance measures in the development of these new forms of transport will be crucial to facilitating their widespread adoption. Possible solutions are • data minimization principle – ensuring that only the data needed strictly for operation is collected and used, meaning no sponsored content on the way to work/home • privacy by default/design – it is the manufacturer’s and fleet operator’s job to ensure appropriate privacy measures are taken • code of conduct – standardization of autonomous vehicle design from a data protection/cyber security standpoint, thus companies must have a plan for keeping user data private and be clear to the consumer about how it will be used • principle of cross border basis – security standards on a supranational level allowing cross-border transportation (especially in the EU) Consumer trends Radical changes in consumption habits has caused creative disruption on numerous markets creating, a new model called the sharing economy. Many of the companies following the new trends are already global players. The essence of the sharing economy is that consumers share their capacity & resource surplus on demand and based on trust, focusing on personal interaction and striving for sustainability. According to projections, autonomous vehicles will also be part of the sharing economy. The new technology is most popular among potential users in developing countries. These consumers expect that the autonomous ecosystems will provide safe, affordable, convenient and personalized transport options. E-drive system New car sales are still mostly dominated by traditional car sales. The proportion of electric and hybrid vehicles is relatively low. However, by 2020 the proportion of electric and hybrid cars will significantly increase and conventional cars will be progressively replaced by them. By 2030, electric and hybrid car sales will have a great influence over the market, and therefore the number of traditional cars is shrinking. PwC estimates that by 2030 thirty-five percent of vehicles in circulation will be powered by electric drive technology. Whereas in conventional cars there are around 4,000 moving parts, electric cars can be assembled from around 320 moving parts. Accordingly, the workforce requirement is different, because it takes seven workers to assemble a conventional car, and only one to assemble an electric car. Previously, mechanics could assemble conventional cars, but e-drive systems require electricians and energy specialists. Alternative power supply The category of electric vehicles breaks down into two subcategories: battery electric vehicles (BEV) and hybrid electric vehicles (HEV). The hybrid group can be further divided into plug-in hybrid electric vehicles (PHEV) and non-rechargeable hybrids. Non-rechargeable or conventional hybrids combine the combustion engine with an electric drive that converts kinetic energy into electric current. In contrast, plug-in hybrids can be charged from an external power supply so they can replace conventional fuel at least partially with electricity generated on a renewable basis. These extended electric vehicles, in addition to an electric motor, also feature a small range extender for optimized power generation, capable of charging the battery so that larger distances can be covered without external battery charging. Electric vehicles use lead acid, lithium ion and nickel-metal hydride batteries or ultracapacity to store energy. Most of the modern plug-in hybrid and clean electric vehicles have lithium-ion batteries, which are justified by their high storage capacity, good power-to-weight ratio, energy efficiency, high performance at high temperatures and low self-discharge compared to lead acid batteries. Due to environmental considerations, in the future sodium ion batteries may be an alternative to lithium ion. The importance of sodium-based batteries lies in offering the same storage capacity but 80% cheaper than lithium-based batteries. This is possible because sodium is much more abundant than lithium. Public transport The aim of modernizing the means of transport in local public transport that still use conventional internal combustion engines is to replace them with purely electric-powered passenger vehicles. Alternative propulsion technologies both support the transition to renewable resources and the reduction of local air pollution. Purely electric drive technology has the most potential, but the disadvantages are high price and limited range. Electric autonomous buses are already being used in the US, Germany and the Netherlands. The most commonly used public transport vehicle in Hungary is the bus, the proportion of which exceeds 50% in local traffic and over 75% in interurban traffic, and therefore the focus is on the introduction of electric buses. In the case of electric buses, charging is the only problem because electric buses are capable of running a daily average mileage of more than 200 km only with frequent charging. Assuming some development of battery technology, the extension of the range and a limited charge (at the terminal station), electric buses purchased during the period 2019-2025 could be used to serve an average daily mileage of 200 km. Electric buses are mainly used for urban public transport. They can be used not only in Budapest but also in larger towns in rural areas. In order to optimally implement the electrification of domestic public transport by 2025, half of the current bus fleet has to be replaced with electric-powered buses, so about 600 new electric-powered buses will be put on the market. Passenger vehicles As a result of novel sharing concepts, the automotive market will face radical change in 2030. The stock of cars could fall from 280 to 200 million in Europe and 270 to 212 million in the United States. While vehicle stock could fall dramatically in Europe and the US in 2030, traffic on the roads will become even heavier. In only a few years’ time, today's norm where most people drive themselves in their own vehicle will only be one mobility concept among many. The growth of low-cost car sharing concepts is an irreversible process. This trend towards ‘sharing’ will be coupled with electrification of drive systems and huge advances in the development of self-driving cars. The autonomous driving concept will first be introduced in taxi services, because human resources are the greatest costs for taxi companies. Driverless autonomous taxis are going will be used at the 2020 Olympics in Tokyo; vehicle testing is already in progress. In China, the penetration of shared and autonomous mobility will happen faster than in the Western world. This could make China the leading market for the transformation of the automotive industry. Transport Logistics costs can be reduced by 2030 by using robots in warehousing and digital trucks. The advent of the digital truck will completely transform how freight is transported on the world’s highways. Imagine a world in which long caravans of large trucks travel in lockstep down major highways while each of the trucks automatically transmits its whereabouts, estimated time of arrival, and load information to its next stop. The warehouse system automatically assigns each truck to a loading dock, where several autonomous forklifts stand ready to unload it. Then they move the load on to another portion of the warehouse, where it is sorted by machine for local delivery routes and loaded onto the proper small autonomous electric trucks for final delivery. Two global trends are transforming the trucking industry. First, efforts on the part of regulators around the world to manage climate change and to save energy and resources are forcing the industry to develop cleaner, more efficient trucks and optimize the use of heavy vehicles. Second, social and cultural changes are opening up new markets and increasing expectations for the efficiencies to be gained through autonomous vehicles and the digitized supply chain. Regulatory trends: Two regulatory mindsets are competing on the global level: OEM incumbents are favoring an evolutionary approach and are developing automated driving functions step by step. Innovation follows SAE autonomy-levels, maximizing profits on every level. Germany is driving EU legislation. Startups on the other hand drive change where legislation is favorable, entering the digital mobility market by developing Level-5/fully autonomous systems (mainly in the US).
Regulatory frameworks play a crucial role in the expansion of the digital mobility market. Legislators have to tackle difficulties integrating autonomous vehicles into existing regulations. Key issues to handle are:
- Autonomous testing standards
- Driving regulations regarding mixed traffic and responsibility for damage
- Cyber security

Two regulatory mindsets/directions/trends are competing on the global level.
OEM incumbents favor an evolutionary approach and are developing automated driving functions step by step. Innovation follows SAE autonomy-levels, maximizing profits on every level. Germany is driving EU legislation.

Startups on the other hand drive change where legislation is favorable, entering the digital mobility market by developing Level-5/fully autonomous systems (mainly in the US).
Connectivity is key to the autonomous ecosystem becoming mainstream. Connection between different vehicles and the infrastructure is made possible by a complex process. Several cameras and sensors are responsible for general detection of the surroundings. The data generated by the sensors is processed by on-board computers and cloud-based solutions that are also responsible for the actions of the machines in the ecosystem. The most important feature of connectivity is the communication between machines via the internet, which enables them to share information concerning road- and weather conditions, and learn from each other. The autonomous ecosystem will cause changes in our habits as regards mobility, and user preferences will move more towards autonomous mobility. Our forecasts suggest that by 2030, more than one in three kilometres driven could already involve sharing concepts. The mobility of the future can be defined with the acronym “eascy” – electrified, autonomous, shared, connected and “yearly” updated.
Electrified – The transition to emissions-free mobility will become a global requirement. Electricity used to charge vehicles will increasingly come from renewable sources to ensure carbon dioxide-neutral mobility.
Autonomous - The development of vehicles which require no human intervention will reduce the use of public mobility platforms and offer individual mobility to new user groups.
Shared – Professionally managed fleets of shared vehicles will reduce the cost of mobility by a significant amount through more efficient use of expensive mobile assets.
Connected – This applies in two ways: communication between cars or with traffic management infrastructure or between vehicle occupants and the outside world.
‘Yearly’ updated – The range of models will be updated annually to integrate the latest hardware and software developments, and react to changing requirements of shared fleet buyers.
The human factor of the autonomous ecosystem is basically understood as the measurable global demand for digital mobility. The changing trends of consumer behavior suggest that digital mobility will be based on technology disruption and will follow the principles of the sharing economy. Global surveys show that consumers expect this new technology to be
- multi-modal
- connected & integrated
- on demand
- experience-driven
- subscription-based
- personalized
- shared

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Ádám Osztovits

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András Kéri

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