3 ECS Key Application Areas

3.1
Mobility

Mobility is a basic human need and Europe’s mobility industry is a key contributor to it. The automotive sector alone provides employment, both direct and indirect, to 13.8 million Europeans, representing 6.1% of total EU employment. 2.6 million people work in the direct manufacturing of motor vehicles, representing 8.5% of EU employment in manufacturing1. The automotive sector is also the driver for innovation in many other mobility sectors in Europe, including aerospace, maritime and rail, but also in other sectors as e.g. farming and industry (advanced robotics).

The key enabling technologies of KDT (sensors, semiconductors, embedded AI enabled software in integrated intelligent systems) are essential building blocks for CO2-neutral and energy efficient mobility solutions including the required energy transformation. But as the microelectronics-based computers, sensors, actuators and communication equipment use energy themselves, also more energy- and cost-efficient electronic and optoelectronic components, interconnected intelligent systems and (AI-based) embedded software, often connected to powerful AI-enabled backend cloud systems (e.g. traffic control systems), are necessary.

Therefore, the research scope encompasses the development of energy efficient mobility grade (for automotive, maritime, rail, aerospace, autonomous vehicle up to offroad and smart farming machinery applications) semiconductor. The have to support also AI based applications. The second important part is the development of the necessary middleware and embedded SW applications, which are often part of a cloud to edge continuum. The third equally important part is the development of the necessary development, verification, and validation tools.

Our mobility is currently in a fundamental phase of change. Mobility is faced with great challenges and at the same time offers enormous potential to help solving essential problems of our world: global warming because of CO2 created by our society (- Green Deal is coping with it -), an ageing society with special needs for easy and accident-free mobility. Therefore, our mobility is subject to a radical ecological (as well as political) change towards its contribution to the European Green Deal as well as towards automated and/or assisted mobility. The interaction with digitisation, urbanisation, connectivity, and individualisation increases the demand for innovative solutions that are based on people's needs like never before. It is important to accelerate the combination of these two developments in a meaningful way in the future.

During the COVID crisis individual transport was largely favoured due to a basic user need, a clean and safe personal environment. Only cars can offer such an environment today. On the other hand, the current energy crisis demands to reduce energy usage also in mobility. Shared and new mobility concepts are going to play an increasingly important role. A major challenge will be to combine this need for individual space in a public or shared mobility environment, which reduces the energy consumption of mobility by more than 20 % compared to today without setting CO2 free or causing more accidents than experienced drivers.

This societal challenge, known as the European Green Deal, is at the forefront of the EU’s priority list. As automotive traffic is currently contributing approximately 14% of global CO2 emissions, CO2-neutral mobility requires alternative mobility systems (battery or H2 fuel cell based wherever possible, also synthetic CO2-neutral fuels are necessary in some applications) for automotive vehicles, ships, and flying equipment. It also needs smart energy-production, intermediate energy storage, energy transmission and charging infrastructure. This is an important part of the energy transformation in Europe. Existing infrastructure must be optimised or replaced, wherever possible the use of existing mobility infrastructure is envisioned.

This ECS-SRIA chapter on mobility is aligned with the proposal for the partnership “Towards zero emission road transport” (2Zero) programme by Horizon Europe to achieve carbon-neutrality in road transport by 2050. There are plans to continue and strengthen this cooperation between 2Zero and the ECS community.

The second societal challenge relevant for the mobility domain focuses on the usage of smart perception, safety and automated mobility solutions and services to provide safe and comfortable inclusive mobility that is also suitable for the elderly, as well as people with special needs. Research, development, and innovation (R&D&I) of embedded AI-based software, sensors and electronic components and systems provide the core of automated on- and off-road vehicles, ships, trains, and airplanes. A special focus requires validation of the safety and reliability of the automated mobility systems in all traffic and environmental situations as there are currently no adequate methods and tools available. Digital twin technology will be crucial to evaluate, develop and update/maintain real-life vehicles. Therefore, the ECS-SRIA chapter on mobility is also closely aligned with the proposal for the partnership “Connected, Cooperative and Automated Mobility” (CCAM) under Horizon Europe.

Additional key aspects of the contribution by the ECS domain to the future of mobility are increasing user value, security, privacy protection features, affordability, and human interaction. Particularly in urban areas, intermodality and technologies supporting the shared principles will be crucial.

3.1.3.1     Strong contribution to CO2-neutral Mobility

Mobility is at the heart of European lifestyle and its economy. Efficient transportation systems are more important than ever, and also help consolidate the European Union and make it more cohesive. However, the promise of freedom offered by road transport is viewed in sharp contrast to a range of concerns about its effect on safety, health, and the environment. Therefore, transport and mobility systems are in the process of a fundamental transformation towards a vision of sustainable, CO2 emission neutrality that involves efficient, inclusive, and seamless solutions. CO2-neutral mobility is mainly using electrical energy; therefore, mobility is also embedded in the European Energy Transformation. The key digital technologies (ECS) are essential for the transition to CO2-neutral mobility.

3.1.3.2     Contribution to inclusive mobility

An additional societal aspect is an inclusive mobility: for decades, disabled people have promoted a universal approach to the design of transport systems to make them more accessible and useful for everybody. In view of the Covid-19 pandemic, this focus on human factors of transport innovation is expected to increase; it will particularly call for smart and intelligent and more and more automated mobility systems enabled by ECS.

3.1.3.3     Strong contribution to fatality-free mobility

Automation and advanced driver assistance system based on ECS have to contribute to a continuous reduction of fatalities of passengers, and improve transportation by different modalities.

3.1.3.4     Protect strong position of European automotive industry and ensure its sovereignty

Mobility is not only a visible expression of Europe’s economic and societal prosperity, but also an important source of that prosperity. According to Europe’s car manufacturers and transporters, the automotive sector employs around twelve million people (approximately 2.6 million directly and close to ten million indirectly), contributing 16% of the EU’s GDP2. Currently, the transportation sector is undergoing a fundamental and complex transformation across all modes. This position is challenged by large US information technology giants and very aggressive and agile Chinese new automotive companies, which are very successful in fully electrical cars as well as new infotainment systems, advanced driver assistance systems and automated mobility.

3.1.3.5     Regain European sovereignty in semiconductors for mobility

Europe is ranked number one in automotive semiconductors. In the automotive value chain, Tier 1’s and original equipment manufacturers (OEMs) are also top global players and intend to gain further market share through close collaboration with semiconductor and embedded software leaders in Europe.

The electronics components and systems (ECS) community will contribute substantially to these tasks by using new technologies, components and systems to target the following topics:

  • Autonomous vehicles

  • Electrified CO2-neutral vehicles

  • Over-the-air (OTA) updates

  • New mobility concepts to reduce overall energy usage (e.g. mobility as a service)

Electrification of vehicles and development of powertrains for carbon-free energy carriers. Enabling technologies are coming from the European ECS industry – for instance, energy-efficient devices, power electronic components and systems, energy (e.g. battery) management systems, and embedded software solutions for power management.

Automated and autonomous vehicles and coordinated mobility to make traffic more efficient and thus reduce pollution by new electronics architectures, smart and connected sensor systems, AI-based real-time software, higher-performance in-vehicle controllers and networks, as well as connectivity devices and advanced embedded software solutions.

Rapid advances in AI and edge computing will ensure Europe can produce a step change in these areas. Automated and autonomous driving, mobility and logistics are high-profile applications where the use of AI technologies is growing very rapidly, affecting both society and industry directly. The European transport industry is being revolutionised by the introduction of AI (combined with electric vehicles). However, AI applications in transport are very challenging, as they typically involve highly complex environments, a large number of possible situations and real-time, safety- relevant decision-making. Leading IT companies in the US and China in particular are providing a challenge to European industry in these areas, and significant effort will be required to safeguard the leading position of the European automotive industry. Hence the development of digital twins is a crucial element to further develop and update all types of vehicles interacting with the environment, with each other and with the cloud.

Revenues related to automated and autonomous driving and connected cars are expected to boom (see Figure 3.1.1), with safety applications (e.g. automatic collision detection/prevention) expected to reach USD58 billion (up from USD18 billion in 2017), autonomous driving (e.g. distance/park/motorway assistant, pilot, traffic sign detection/ recognition) set to reach USD55 billion (up from USD14 billion in 2017) and connected services expected to reach USD43 billion in 2022 (up from USD21 billion in 2017).

Figure 3.1.1 - Forecast growth by market vs. EU GDP growth (Source: Goldstein Research)3

There will be a need to more intensively monitor, interact with, and update the car remotely. Software upgrades need to be done over-the-air (OTA). Semiconductors have a shorter lifetime than cars and hence it is needed to predict their end-of-life and to replace them on-time before the car breaks down.

3.1.3.6     Regain European sovereignty in embedded software for mobility

All of the four mobility megatrends (electrification, autonomy, connectivity, shared mobility) highly rely on leading-edge software. Especially the car industry needs to face this new software-driven value chain. A typical modern vehicle likely has a software architecture composed of five or more domains (body, chassis, ADAS…), together comprising hundreds of functional components in the car and in the cloud. Currently, OEMs are constructing a complex software architecture with various software providers ending up in a complex scenario with a broad set of development languages, operating systems, and software structures/elements. Up to now no single software platform (middleware) on the market can meet the requirements of CCAM. The domain-based hardware architecture is rapidly evolving towards a zonal architecture, where the software architecture, implementation and the corresponding development environment needs to be compatible. A middleware layer has to separate the hardware layer from the software layer and allow faster time-to-market to standardised interfaces.

The work on the mobility challenges will help to protect the sovereignty in the digital heart of mobility devices (passenger cars, trucks, …). Currently Europe has a leadership in the embedded software in all kinds of vehicles. This is endangered by the push of the big global IT companies into the embedded IT systems of the vehicles. Europe has to protect its leadership in creating a next generation of middleware and operating systems prepared for the significantly increased complexity of CO2-neutral automated and assisted vehicles.

3.1.3.7     Convergence of automotive and energy eco-system

Electrified cars are becoming an integral part of the European energy eco-system. Vehicle batteries will be used as intermediate storage for electrical energy (bidirectional charging). Vehicles will even produce electrical energy (photovoltaic panels on car roofs or from heat-pumps), which will be partially send to the grid. This has severe consequences for the requirements of the electrical and software systems in the vehicles. Their operation hours over the intended lifetime of the vehicle are significantly increasing. Up to now, the lifetime for the components of vehicles is about 8000 h, which reflects the hours a typical vehicle is driving. As the vehicle will soon become an integral part of the grid, its total number of operating hours will be the total number of hours per year (both running and connected-to-the-grid time) multiplied by the expected lifetime of the vehicle in years. This means an increase of lifetime of the effected components (as in the bi-directional charging or the necessary embedded control software) by a factor of 5 to 15. This convergence of the automotive and energy eco-system creates also large challenges in the validation. It requires significant use of digital twins in the simulation, as it is not possible to do duration testing over 10 years prior release of a component.

3.1.3.8     Digitalisation in maritime industry

The EU’s maritime industry is characterised by high value-added expertise, rapid innovation, rigorous safety standards and a leading position in green technologies. A strategy to further build on these strengths will ensure that the EU retains its competitive position in the global maritime industry and reaps the rewards in terms of jobs and wealth creation.

3.1.3.9     Digitalisation in aerospace and rail industry

The current leading position of the European aerospace and rail industry will require a further shift to the greater autonomy of planes, trains and infrastructure, and increased trustworthiness of radio and other communication technologies. Therefore, this shift is also strongly dependent on progress in key digital components and AI-based real-time software.

An important priority of the European Commission, in its Communication on the European Green Deal, is ‘’accelerating the shift to sustainable and smart mobility’’. This will require a strong boost to multimodal transport, automated and connected multimodal mobility, a ramp-up of the deployment of sustainable alternative transport fuels and less polluting transportation, especially in cities.

3.1.3.10     New resource optimised mobility modes

New means of transport systems and interaction among different providers (public/private), including other transport modes (multimodal transport for passengers and goods), will be enabled through further development of new and harmonised vehicle-to-everything (V2X), logistics operation software, traffic management devices and guidance systems to enable mobility-as-a-service (MaaS). Easy access to these systems for users will guarantee the highest standards of privacy, to avoid potential impacts caused by the general data protection regulation (GDPR), since information (about origin, destination, financial data, etc) needs to be shared. Software drives tomorrow’s mobility and transport innovations.

The Green Deal and digitalisation are significantly influencing the ECS-SRIA in the mobility domain because of one overall objective: the reduction of CO2 and other emissions, and ensuring inclusive, safe and secure mobility for an ageing global society. This leads to five challenges in R&D&I for mobility.

Five Major Challenges have been identified in the mobility domain:

  • Major challenge 1 (climate and energy): Enable CO2-neutral (electrified or sustainable alternative fuels based) mobility (passenger cars, trucks, airplanes, ships, bicycles, tricycles, wheelchairs, drones, and mobile off-road machinery (e.g. for smart farming or mining)) and required energy transformation.

  • Major challenge 2 (digitalisation): Enable affordable, automated, and connected mobility for passengers and freight on road, rail, air, and water.

  • Major challenge 3: Provide modular, scalable, re-usable, flexible, cloud-based, safe&secure end-to-end software platforms (operating system and middleware) able to manage software-defined mobility of the future, sometimes labelled as “CAR-OS”.

  • Major challenge 4 (validation): Provide tools and methods for validation and certification of safety, security, and comfort of embedded intelligence in mobility (using also digital twins).

  • Major challenge 5 (real-time data handling): Achieve real-time data handling for multimodal mobility and related services.

The results of R&D&I from challenge 1 will be used in green CO2-neutral vehicles of all kinds, some of them integrated into the 2Zero EU partnership, and therefore roadmaps and research programmes are (and will be) aligned. The SRIA of the private public partnership CCAM activities working on “Connected, Cooperative & Automated Mobility” is well aligned with this SRIA in the major challenges 2 to 5 as the key digital components, tools and systems described in this SRIA are essential building blocks in the challenges in CCAM. The outcome of the research on the challenges described here will be used in partial or fully automated vehicles for the CCAM EU programme. Therefore, roadmaps and research programmes are of 2ZERO, CCAM, KDT and BDVA are (and will be) aligned.

3.1.4.1     Major Challenge 1: Enable CO2-neutral (electrified or sustainable alternative fuels based) mobility and required energy transformation

Status, vision, and selected outcome

Worldwide efforts on the regulation of pollution and CO2 emissions are leading to a strong increase in the electrification of vehicles, either with batteries (“battery electric vehicles”, BEVs), “hybrid electric vehicles” (HEVs) with petrol or diesel engines or using fuel cells. Possible scenarios developed by BIPE4 in France are shown in Figure 3.1.2. Depending on the evolution of regulations in particular, the split between the various energy sources could be significantly different between the scenarios in figure 2. However, the most probable scenario is that of the “Green Constraint”. But currently there are discussions about bans of fossil fuel engines even as soon as 2035, therefore the data are expected to change.

Figure 3.1.2 - Sales structure of cars 2018 and 2035 (4 scenarios) (Source: PFA France 2018)

Looking in more detail at the difference between low voltage systems (particularly 48V) and high voltage systems, there are six important observations that can be made:

  • All new cars in Europe will be electrified by 2035.

  • The proportion of electrified cars in the world will reach about 70%.

  • Low-voltage systems will take about 60% of the market, high-voltage will take the rest.

  • Around one-third of the market will require on-board chargers for high voltage in the range 400–1000V.

  • Fuel cell electric vehicles will still play a significant role in long-haul trucks and trains, as well as in airplanes, ships, and drones by 2035.

The expectation is that the overall electrification scenario will lead to massive changes in the supply chains and the distribution of competences. In the field of power electronics, Europe is now in an excellent position and its industry needs to organise itself to ensure it benefits from the opportunity.

An important aspect in the CO2 reduction is the speed of reduction. Selling new cars with best performance characteristics will only show an effect in the medium and long term. Any solution that improves the existing parc of 250 million cars in the world would have a much higher impact.

FISITA has explained in a recent study how, for example, car sharing, more efficient tires, teleworking and better lubrification could add-up to significant and instantaneous CO2 reductions. In this respect, the electronics industry should regard solutions that support rapid deployment of CO2 reduction initiatives.

The focus area has the following topics to address:

  • Modular, flexible, and scalable platforms and electrical/electronic (E/E) architectures.

  • Hardware upgradability.

  • Exchange of existing components and systems by higher efficient modules.

  • Reconfigurable and adaptable software architectures.

  • Software updateability (including over-the-air, OTA).

  • On-board technologies (devices, actuators and sensors, virtual sensors).

  • Embedded intelligence (AI-powered and AI-enabled intelligence):

    • Control software, real-time capable algorithms.

    • Fault-tolerance, fail-operational concepts.

    • Cognitive vision.

  • New control software is required to take full advantage of new solid-state batteries so that they have an extended lifetime, as well as a higher driving range in vehicles. As lifetime is key for batteries used in mobility systems, tools for accelerated lifetime testing, diagnostic systems as well as control systems that can extend the lifetime and limit degradation, are essential for the success of electrified green mobility. New power electronics based on silicon carbide (SiC) and gallium nitride (GaN) devices are needed to ensure energy-efficient operation. AI and model-predictive control algorithms, supported by high-performance, multi-core, real-time operating systems, has to offer the necessary intelligence based on ultra-low power/high-performance control units.

  • Similarly, advanced control methods for fuel cell-based vehicles (mainly in trucks and buses) that both minimise degradation and maximise efficiency are crucial. For example, predictive control schemes that take into account forecasts on e.g. route, traffic, weather, etc. are necessary. State-of-health monitoring systems (virtual sensors) as well as adequate new sensors to measure the operating conditions within fuel cells without negatively influencing their operation, are required.

  • For both electric battery and fuel cell-based mobility, new safety concepts using (AI-based) IoT diagnostics must ensure the safety of these systems, especially in accident situations.

  • Low environment impact of new technologies in terms of energy consumption at production, deployment, use and end of life treatment.

  • Reduction of sensible materials such as rare earth materials.

  • Recyclability.

  • Efficient and fast charging and filling of alternative energy into green vehicles is another critical research topic.

  • The conversion of renewable energy into green energy, as electricity stored in vehicles or H2 or alternative fuels, also needs efficient electronics with real-time embedded software communication with the power grid to minimise the need of new charging/filling infrastructure, which is one of the cost drivers limiting the speedy success of green mobility.

  • Smart Battery: with the batteries in electric vehicles being the most expensive and life-time critical parts, future battery systems will be equipped with sensing technology, intelligence, and communication systems to monitor their own health and record their lifetime dataset. This enables better usage of the batteries as well as optimised second life concepts.

  • Power electronics (fast-switching elements, wide bandgap materials, low power, etc.).

  • Predictive diagnosis and maintenance (including recovery strategies, fault detection and localisation, surveillance sensors, etc.).

  • Cloud/edge/fog processing approaches.

  • Distributed logistics systems for smart farming, movers and shuttles.

  • Standards, including communication and interoperability standards, electromagnetic spectrum, and bandwidth management, charging units, car access systems, etc.

  • Reliable and human-like perception systems.

  • Tailored ECS-enabled solutions for disabled people (supporting robots, smart wheelchairs, etc).

  • Proof of robustness and trustworthiness of architectures and quantification of the operational risks.

  • Collaborative and self-organised multi-agent systems, e.g. in logistics applications also covering cooperation between land and air vehicles.

  • Bio-inspired transport solutions and systems.

Digital innovation is key to ensuring inclusive mobility for persons and goods by providing mobility access to all, with a focus on special needs, by reaching 90% of the EU population compared to the current 60%. As targeted by CCAM, this can be achieved through assisted vehicles by 2050.

By 2050, 67% of the population is expected to live in urban areas. As cities become bigger and smarter, this trend will lead to new opportunities for tailored and specialised vehicle design specific to urban users, including the needs and operations of commuters, as well as ride-hailing and last-mile delivery.

New vehicle concepts and ECS-enabled architectures should lead to flexibility, scalability, and modularity - while featuring safety, security, and reliability - to ensure urban-readiness (appropriate range, compatibility with charging infrastructures, ease of parking and operations, etc) in all kinds of urban and suburban areas, most likely with different implementation levels of infrastructure and smart technologies. Additionally, it is assumed that these vehicles will not have to be designed for high-speed operation and long range and can easily be charged sufficiently fast and comfortably to meet the daily needs of urban and suburban mobility usage scenarios. This aspect may also include sharing concepts, and consideration should also be given to use by the elderly and disabled.

Another important aspect is the need for reliable and efficient wireless communication technology combined with different types of sensing systems to achieve efficient traffic, and increase safety as well as reduce fatalities. This further sets requirements on components and systems for wireless communication to achieve ultra-high reliability and resilience as well as to meet challenging performance and latency demands.

The challenge targets the following vehicle categories:

  • Passenger cars (including light four- wheelers, M1/M2 category).

  • Trucks (including power-driven vehicles having at least four wheels used for the carriage of goods (N1), agricultural and forestry tractors, and non-road mobile machinery (T)).

  • Ships.

  • Airplanes.

  • Motor vehicles with less than four wheels (L category).

  • Off-road vehicles (G).

  • All kind of unmanned air vehicles (such as drones).

  • All kind of manned light air vehicles.

  • Special-purpose light vehicles (air, land, water).

The developments described above ask for innovative mobility solutions in the years to come, affecting European society::

  • Urban personal, light personal and freight mobility (including innovative micro-vehicle designs suitable for urban/suburban commuters’ needs, with the option for usage within shared mobility schemes. Such micro-vehicles would also be capable of interfacing with urban collective transport systems (i.e. easy access to buses, trams, and trains for last-mile transfers to achieve full intramodality)).

  • Light and flexible multi-passenger vehicles (e.g. collective, or individual, owned or shared up to M1 category) with robust safety measures for passengers and vulnerable road users, and including specific features to facilitate shared use such as autonomous-capable vehicles with automated relocation to charging points or areas with insufficient vehicle density.

  • Log-haul and right-sized vehicles and tailored ECS for commercial uses, such as for long distance, last-/first-mile delivery, construction and maintenance support, which are suitable for urban scenarios.

  • Connected and automated mobile machinery to optimise harvesting and reduce accidents.

3.1.4.2     Major Challenge 2: Enable affordable, automated, and connected mobility for passengers and freight on or off road, rail, air and water

Europe envisions fatality-free transportation as well as seamless mobility choices for its citizens, particularly in view of the aging society. Moreover, the transport industry in Europe in general aims to maintain its leading position by offering sustainable solutions for safe and green mobility across all transportation domains – automotive, avionics, aerospace, maritime (over water as well as under water transport) and rail. Europe’s strength lies in its established expertise in developing complex electronic components, cyber-physical systems, and embedded intelligence. However, hurdles related to autonomy, complexity, safety, availability, controllability, economy, and comfort need tackling as automation increases.

The overall vision is to achieve always-connected, safe and secure, cooperative and automated transportation systems using highly reliable and affordable European-made electronic components and systems. These systems will also incorporate new human-machine interaction technologies.

For the road sector, the key objectives are (a) to reduce the number of road fatalities and accidents caused by human error to zero by 2050, (b) to ensure automated transport introduces no additional road fatalities, and (c) to decrease validation costs down to 50% of development costs from the current 70–80%. Key Digital Technologies are crucial for achieving these goals and supporting the ambitions of the Horizon Europe Partnership on Connected, Cooperative and Automated Mobility (CCAM). Collaborations in and across industrial domains, learning from operational field data, and joint strategic actions are essential. No single entity can singlehandedly manage these significant R&D efforts.

For waterborne transport, as automation progresses ships will become fully connected, globally. Remote vessel monitoring is already possible, allowing for condition-based maintenance. Building on increasing onboard automation, the remote operation of vessels will become possible, eventually moving towards full autonomy for vessels. The wider use of unmanned autonomous vessels (UAVs) – either aerial, underwater or on the surface – will increase the flexibility and energy efficiency of operations.

For avionics and aeronautics, automation is paving the way for more efficient flight management, reducing pilot workload, and enhancing predictive maintenance, which collectively promises safer and more efficient air travel. Additionally, Urban Air Mobility (UAM) is revolutionizing cityscapes, with automation enabling flying taxis and drone deliveries, presenting a transformative solution to urban congestion, and offering a new dimension to urban transport.

For the rail sector, automation is driving the development of driverless trains, optimizing track usage, enhancing scheduling accuracy, and ensuring safer and more punctual journeys for passengers.

Connected, cooperative and ultimately automated mobility will play a central role in shaping our future lives. ECS will enable different levels of partial, conditional, highly and fully automated transportation, posing new challenges for traffic safety and security in mixed scenarios where vehicles with different automation levels coexist with non-automated vehicles. Both stepwise automation (“conversion design”) and full automation (Society of Automotive Engineers, SAE, level 5: “purpose design”, e.g. a people mover in a structured environment), have been developed to the prototype level and are being deployed in field-operation tests right now. Nonetheless, these solutions need to be further explored and improved towards safe and reliable capabilities in extended operational design domains. Additionally, cross-fertilisation with other industrial domains such as Industry 4.0 and evolving communication technologies (5G/6G) is essential.

As the proportion of electronics and software, considered as a percentage of the total construction cost of a vehicle, increases, so does the demand for the safe, secure, reliable, and unhackable operation of these systems. In addition, privacy protection is paramount for car owners and drivers/operators. This demands robust and fail-operational technologies that deliver intrinsically safe operation and dependable fall-back position from component to subsystem, and provides a solution for problems in interaction with the cloud. Also, multi-core-based platforms and sensing devices, combining advanced sensing in harsh conditions, novel micro- and nano-electronics sensors, advanced sensor fusion and innovative in-vehicle network technologie are neededs.

Key elements of ECS for cars that need to be developed are shown in Figure 3.1.3.

Figure 3.1.3 - ECS-based components of automated vehicle

The following research, development and innovations areas and their subtopics have been identified:

  • Dependable and affordable environment perception and localisation sensors, and V2X communication. Attention should be paid to sensor interference, more in particular the robustness of sensors to environmental conditions, to interference by other sensors and to malicious interference.

  • Integrated sensing and communication systems to further evolve towards fully automated transport and safeguarding VRU’s (Vulnerable Road Users) in all type of traffic situations.

  • Centralised service/function-oriented hardware/software architectures, including open APIs, for road vehicles, ships, trains that are supported by the cloud and edge computing via 5/6G.

  • Dependable and reconfigurable hardware and software, including remote access and Over-The-Air (OTA) software upgrades.

  • Hardware and software platforms for control and higher performance in-vehicle networking (up to 25Gbit/s) units for automated mobility and transportation (including support for AI), for example the usage and adaptation of IoT integration platforms, also for automated and connected environmentally friendly vehicles.

  • New developments towards higher performance and efficiency: These are also required to ensure the reliability and safety of the power electronic components and systems for the drivetrain and charging systems, as well as for steering, breaking/suspension/air condition control in automobiles, trains, ships, and flying equipment.

  • Trustworthiness of vehicles’ data.

  • Interaction between humans and vehicles.

  • Active safety systems.

  • Advanced AI-based and predictive control methods to create new active safety paradigms for the next generation of automated vehicles, e.g. to operate beyond the boundaries typical for the current generation of stability controllers and chassis control systems, when this is needed to prevent road accidents. This also implies a redefinition of the software architecture to integrate the chassis control and driving automation functions. The current generation of chassis control systems – which will be used in the first generation of automated vehicles – is designed to keep the vehicles within limits that are desirable for human drivers, but further research is required to assess the new active safety options (e.g. race driving techniques to prevent crashes in emergency conditions) enabled by driving automation.

  • V2X-based chassis control systems, e.g. vehicle stability controllers using the road curvature profile ahead, and other infrastructure-related information, e.g. tire-road friction information from preceding vehicles.

  • Multi-functional cross-domain and preview-based control software implementations, e.g. powertrain and brake-by-wire controllers concurrently managing energy efficiency, active safety, and comfort aspects (e.g. powertrain torque distribution to induce desirable pitch in braking, compensation of the longitudinal acceleration oscillations caused by road irregularities through road preview-based control of the powertrain torque).

  • Vehicle hardware/software and robotics to improve comfort in parallel with safety.

  • (Predictive) health monitoring and lifetime analysis for the perception and control systems (including all required sensors, V2X systems and localisation systems) and AI components of (highly) automated vehicles used in the operational phase.

  • Connected maritime systems and automated transport.

  • Smart and autonomous ships.

  • Driverless trains.

These requirements result in completely new hardware and software architectures for the control systems due to exploding sensor data volumes, as well as new power saving hardware and software components. This requires a new decoupling from hardware with drivers and operating system, from the application components, adaptive AI-based routing and control algorithms, multimedia components and many more, and at the same time a co-designed process of interface developments. Therefore, the Major Challenge 4 was introduced to create a common middleware architecture and implementation.

3.1.4.3     Major Challenge 3: Modular, scalable, re-usable, flexible, cloud-based, safe&secure end-to-end software and hardware platform for the software-defined vehicle of the future

Today’s mainly hardware-defined cars are rapidly transforming into software-defined transportation platforms. Currently, OEMs and their suppliers are developing automotive software modules in isolation, ending up in a complex software architecture which does not scale at all. The following figure (McKinsey and Company) illustrates the state-of-the-art in how proprietary platforms are built at present. Even though integration among different domains and vehicle systems is essential to unlock new use cases, companies are currently missing an end-to-end platform to easily connect everything together.

Figure 3.1.4 - Layer structure of Software Defined Vehicle building blocks.

Currently, automotive software developers working on different software stacks across a vehicle do not coordinate their activities on a regular basis. Furthermore, it is difficult to align software updates and patches across modules. Because of the rapid transformation to software-defined vehicles (driven by new vehicle functions, features, properties), the automotive industry is facing a widening and unsustainable gap between software complexity and productivity (see figure 3.1.5 below). To succeed in this dynamically changing environment and to be globally competitive, companies need to minimise (or at least limit) the complexity by reducing the effort required to develop and maintain software. Consequently, the current software operating model needs to be revisited in terms of:

  • Architecture, design, requirements.

  • Development methodologies (e.g. agile-at-scale, or fundamental changes in development and software testing).

  • Software performance management, toolchain infrastructure.

  • Where software is developed within the organisation, including locations, and partnerships involved.

Figure 3.1.5 - Gap between software complexity and productivity.

Ultimately, an end-to-end software platform, consisting of virtualisation, operating system and a middleware layer with standardised interfaces abstracting the hardware layer for the application and function software layer is strongly needed to be able to manage the rising software complexity and to develop future vehicles in an effective and efficient manner. Software should be truly integrated end to end, software modules should be developed on a common code base, and a primary robust operating system should be able to cover all major systems throughout the vehicle.

Figure 3.1.6 - Example of architecture decoupling HW and SW and supporting the vehicle middleware layer.

The following topics have been identified for essential research:

  • Development of a scalable, cloud-capable, and modular target architecture that supports decoupling of hardware and software and features a strong middleware layer (see illustrative example, figure 3.1.6). The target platform (middleware) to be developed needs to support current and future operating systems (proprietary, open-source) and also different E/E architectures (domain-oriented, zone-oriented etc.).

  • Development of a neutral SDK (cf., the smartphone world before and after the iPhone of 2007) which allows any software application developer to develop and test independently of hardware and operating system.

  • Abstraction of the complexity of underlying hardware, middleware, kernel, interfaces, and drivers into simple to use and to re-use, robust, safe&secure APIs.

  • Support of safety and security according to automotive standards (safety-criticality is the main difference to the smartphone and consumer electronics market).

  • New software development methodologies (e.g. agile-at-scale).

  • Eventually, the targeted software platform should basically fulfil and feature:

    • ROS1 and ROS2 compatibility.

    • Hardware SOC abstraction, runs on x86 and ARM.

    • freedom of choice of SOC.

    • Middleware abstraction simplifies the use of complex middleware interfaces.

    • Hard real-time execution and real-time logging of data.

    • Fully deterministic software execution.

    • System safety enabled through managed nodes with lifecycle management.

    • System security through process-level security, encryption, authentication.

    • Support for automotive hardware, i.e., ECUs and automotive sensors.

    • Functional safety certification (ISO 26262, SEooC, up to ASIL D).

    • Appropriate testing methods, e.g. condition coverage or integration tests.

    • Development environment, tools, toolchains.

    • Complete and integrated solution for both intra- and inter-ECU communication.

    • Integration of common frameworks such as AUTOSAR, Apex.OS and others.

    • Simple to integrate into custom frameworks.

    • Support for today's most relevant protocols for automotive ethernet.

    • Capable to handle large amounts of data efficiently.

    • High-performance communication with low runtime consumption

    • Ensuring compatibility to SIMPL5 (cloud-to-edge federations and data spaces made simple). SIMPL is the smart middleware that will enable cloud-to-edge federations and support all major data initiatives funded by the European Commission, such as common European data spaces.

3.1.4.4     Major Challenge 4: Provide tools and methods for validation and certification of safety, security, and comfort of embedded intelligence in mobility

To achieve the EU-wide goal of zero fatalities by 2050, active safety systems and automated vehicles are necessary (the term “vehicle” here covers mobility systems on land, water and in the air: cars, trains, ships, airplanes, smart farming and other off-road vehicles). Although several technology demonstrators for highly automated vehicles already exist, there is a severe lack of cost-effective, commonly accepted verification & validation (V&V) methods and tools. Winner et al. predict that more than 400 million km of road driving would be required to statistically prove that an automated vehicle is as safe as a manually driven one, implying that a proven-in-use certification by performing physical tests on the road is no longer feasible.

This lack of effectively applicable V&V methods has created a major barrier for the market introduction of these systems. The development and use of Digital Twins is becoming a cornerstone for future development and updates of this type of complex automated systems, interacting with the cloud. Meanwhile many experts in Europe, as well as in many other countries of the world, work together under the guidance of UN/ECE to create standards for the approval of ADAS and AD functions in mobility. The draft of the Regulation (EU) 2019/2144 for ADAS functions is approved and contains definitions for the expected functionality of many ADAS functions, as well as first indications of how to prove them. The associated ADAS and AD functions are Lane Departure Warning System, Advanced Emergency Braking on Heavy Duty Vehicles, Speed Limitation Devices, Reversing Detection, Pedestrian and Cyclist Collision Warning, Blind Spot Information System, Emergency Lane Keeping System, Advanced Emergency Braking on Light Duty Vehicles, Protection of Vehicles against Cyber Attack, Intelligent Speed Assistance, Emergency Stop Signal, Alcohol Interlock Installation Facilitation, Driver Drowsiness and Attention Warning, Driver Availability Monitoring System, Event Data Recorder, Systems to replace driver's control; systems to provide the vehicle with information on state of the vehicle’s surrounding area and Platooning.

The main challenge is the tight interaction of these safety-critical automated systems with their environment. These interactions get more complex the higher the automation level gets. This means that not only the correct functioning of the automated cyber-physical mobility system itself needs to be tested, but also its correct reaction to the behaviour and specifics of its surroundings. This leads to a huge number of potential scenarios that every automated mobility solution will have to handle in a safe way. It is important to take not only the commonly occurring scenarios encountered by the mobility systems as vehicles, trucks, airplanes, ships etc. in account, but also the occurrence of safety-critical events during these scenarios. Many of these safety-critical events fortunately do occur only seldom, but that makes it even more difficult to test the correct reactions of the automation systems in these situations.

Many highly automated cyber-physical systems have adopted machine learning (ML) and AI to enable autonomous decision-making and render applications smart. While the use of ML and AI components offers great promise for improving our everyday lives in many, sometimes unimaginable, ways, it also brings a host of very difficult verification, validation and certification challenges in the context of safety- critical applications. The opacity of ML/AI components requires the development of completely new V&V techniques, and to accordingly extend existing V&V methodologies. It is important to not only secure stable solutions based on ML, but also determine how to exploit increased learning based on new data, and to update existing vehicles with updated algorithms using the additional learning from new data, while guaranteeing no side-effects.

Figure 3.1.7 - Validation framework for automated vehicles (Source: AVL List GmbH)

Modern highly automated cyber-physical systems increasingly dynamically evolve after their deployment, and OTA updates and upgrades are becoming necessary in such systems. This requires a tight integration of the analysis of data from the field and fast software changes with subsequent over-the-air updates of the vehicle in the field, and ensure that any safety and/or security relevant problems identified in vehicles in the field are solved as soon as possible at all vehicles in the field. This requires new methods and trustable tools for these updates and upgrades, together with the respective re-verification and re-certification approaches, necessary to avoid negative impacts on both safety and security. These verification and validation tests must be integrated in fully automated CI/CD pipelines.

Automation functions of vehicles rely on environment sensors, such as cameras, lidar, radar and ultrasonic sensors, as well as communication to other vehicles or infrastructures. As these safety- relevant components may degrade over time or be exposed to cyber-threats, accelerated reliability and cybersecurity test methods are required. This will need further diagnostic devices to check the reliability of hardware, sensors, and their software.

The role of the driver and any additional passengers in an automated vehicle is completely changing, and therefore new test methods and tools are necessary to ensure comfort and perceived safety (societal acceptance). These are already in the early development phases in terms of new functionality and their safety.

Many of the above issues are mentioned in existing or upcoming automotive standards for cyber-physical systems – for example, Safety of Intended Functionality (SOTIF), ISO 26262 and UL4600 (see Fig. 7). As none of these standards are mature enough to certify fully automated vehicles with reasonable effort, close cooperation between the standardisation committees and the research consortia will be necessary.

The expected outcome is twofold:

  • Digital innovation to increase road safety as specified in the CCAM programme: reduce the number of road fatalities and accidents caused by human errors to zero by 2050, as well as ensuring that no additional road fatalities are introduced by automated transport.

  • Reduce validation costs down from the current two-to-five times of the implementation of automation functions in mobility by 60–80%.

To ensure the safety, security and comfort of automated mobility systems consisting of embedded AI-based software, sensors, and actuators, as well as processing platforms in vehicles, ships, trains, airplanes and off- road vehicles, several verification, validation, and certification toolchains are necessary. These should ensure the safety, reliability, security and comfort for passengers and the surrounding traffic participants based on costs that do not exceed those of the design and implementation of the following functions:

  • Verification of components of automated mobility systems as environment sensors/ communication systems, perception systems, environment awareness, route planning and actuator systems, diagnostics devices and black box monitoring systems. A special case here is the use of consumer-grade components in vehicle automation. Test concepts and tools have to be developed on several levels:

    • Perception system tests focusing on an adequate functionality of sensors and the fusion of several sensor inputs.

    • Manouver planning route decision and track control systems testing.

    • Complete automated vehicle, airplane, ship etc., in the defined operating environments (ODDs).

    • Correct and secure communication with other traffic participants and/or traffic operators.

  • Validation of complete automated vehicles to perform safely and securely, and to provide comfort for passengers as well as other traffic participants in the specified operation design domain (geolocation area, weather conditions, road/sea/air conditions, etc.).

  • Validation of the reliability of all components as well as their interaction as a complete automated cyber-physical system in the specified operation period.

  • Validation of the safety, security, reliability, and comfort for the deployment of OTA update packages for automated on-road or off-road vehicles, trains, ships, and airplanes.

  • Verification of the completeness and reliability of training datasets for machine-learning and AI algorithms used in automated cyber-physical systems.

  • Validation of the accuracy of simulation models in the specified operational design domain (ODD) used in virtual validation toolchains.

  • Development of Digital Twins (for example for vehicles, trucks, drones, ships, airplanes, sensors, pedestrians, environment etc.) for validation of new concepts, verification of Car-2-Cloud interactions and preparation of updates of automated vehicles.

Validation toolchains, their components and underlying methods should lead to safe, reliable, and secure argumentation, describing why the performed tests resulted in the estimated residual risk for automated cyber-physical systems for on-road or off-road vehicles, ships, trains, and airplanes. Optimisation methods can be used to balance multiple design objectives – e.g. ensure that the residual risk remains below a certain limit (such as stipulated by regulatory bodies) while meeting financial design targets. The verification, validation and certification tools and methods may be used for cyber-physical systems with different levels of automation.

A special focus is on the verification, validation and certification of embedded AI-based systems, and the required training data for the respective machine-learning algorithms. Ecosystems for the creation and maintenance of reliable labelled data are envisioned. To integrate with different legacy systems, eco-systems supporting open platforms are required.

Virtual validation, or more concretely scenario-based virtual validation, is considered a cornerstone for the verification, validation, and certification of vehicles. Two aspects are essential here: (i) scenarios representing the most relevant situations; and (ii) reliable simulation models.

Scenarios may be derived from requirements of safety analyses, extracted from naturalistic driving, or synthetically created using gaming theory-based methods with a defined relevance. Statistical safety evidence from scenario-based verification and validation derived from naturalistic driving is needed. Also, here the establishment for open platforms and ecosystems for the creation and maintenance of reliable scenarios is encouraged. The definition of performance (safety, security, reliability, and comfort) indicators for different automation functions and SAE levels (in the case of road vehicles) is necessary. Again, ecosystems to share these data are useful.

Reliable simulation models for environmental sensors, vehicles, drivers and traffic participants, as well as traffic, are vital. The development of these models, and the corresponding test systems, are essential. To test safety-critical scenarios using real vehicles in a safe environment requires the creation of stimulators for the different environmental sensors under different weather, traffic and road conditions. The verification, validation and certification of vehicles will be carried out with a combination of virtual test environments using model-in-the-loop (MIL) and software-in-the-loop (SIL) in the cloud with massive parallel processing in order to allow for testing of very high numbers of scenarios in combination with different critical events and varying ODD conditions as sun, rain, fog, snow etc., mixed virtual/real environments (vehicle-in-the-loop (VIL), and hardware-in-the-loop (HIL)), as well as a proving ground for real-world public road testing. Road testing will result in amounts of data larger than 20 TB per hour per vehicle, and therefore adequate data acquisition, management and (cloud or on-premises) evaluation systems capable of handling the specific data types of the sensors are critical (although these do not exist yet). Additionally, OTA data collection from in-use operations is required to continuously collect unknown scenarios that can be fed back into development to improve the quality of the systems.

Additional challenges covering this topic can also be found in Chapter 2.3 (Architecture and Design: Methods and Tools) and Chapter 2.4 (Quality, Reliability, Safety and Cybersecurity) of this SRIA.

3.1.4.5     Major Challenge 5: Achieve real-time data handling for multimodal mobility and related services

To enhance citizens' health and quality of life, European municipalities are progressively restricting cars with conventional powertrains from city centres in favor of sustainable urban land use. At the same time, in view of the rising demand for individual accessibility, flexible transit and fast delivery, the EU emphasises the importance of multimodality in its transport strategy. This approach combines collective and individual solutions, ranging from micro-mobility, such as e-scooters via car-sharing and ride-pooling, right up to long-haul transport systems through common hubs, platforms and systems for booking, customer services and payment. In the future, Europe will aim for diversity beyond road transport, exploring high-speed rail or electric aircraft. However, challenges persist, including limited peak capacities, missing last-mile connections and isolated mobility-as-a-service system. These bottlenecks impede efforts to decrease travel times, streamline supply chains, and reduce single occupancy trips. Sharing services will play a pivotal role in enhancing public transport flexibility, complemented by innovative solutions like taxi and delivery drones or guided transport systems such as hyperloop solutions that can be expected to fill the gaps in the time, cost, and green environment map.

Recent global events such as natural disasters have spotlighted potential vulnerabilities in this vision. Highly connected and infrastructure-based mobility solutions show limited resilience against flooding and wildfires. It is a pressing priority for mobility service providers to develop and deploy transportation that is both flexible and safe, merging the convenience of multimodality with stringent health and environmental standards while being CO2- and emission-neutral at the same time. The same applies to making autarkic heavy vehicles and machinery for rescue and clean-up operations zero-emission. In another sense, multimodal mobility could also mean putting services and deliveries on wheels, which so far would have required people to travel to places, even if they are elderly or disabled. Having robotic functionality, ad-hoc networking capabilities and a battery as mobile electricity source on a tractor might provide just the right level of resilience that will be needed for future emergencies, and make full use of the opportunities of automation, connectivity, and electrification in a new way.

As pointed out by the EU-funded Coordination and Support Action “Action Plan for the Future of Mobility in Europe”6, the vision of a truly integrated and seamless transport system for people and freight must be developed and implemented, and the full potential of transformative technologies has to be exploited. This can only be achieved if user-centredness, cross-modality and technology transfer become the focus of efforts for all stakeholders in transport.

  • Design a low/zero-emission, safe and accessible transport system tailored to user needs expectations, defining user profiles and mobility patterns, and identifying technology options.

  • Enable mobility everywhere for everyone through the technological development of, for example, sensors, AI, machine learning, predictive maintenance, safe and secure vehicle software, and electronics.

  • Enhance efficiency and capacity in rail projects for automated maintenance and transfer of goods between modes.

  • Create intelligent decision-support systems for passengers and transport operators that enable smart travel demand management.

  • Achieve real-time data handling for multimodal mobility and related services.

  • Develop convenient sharing concepts through automated maintenance of vehicles and define approaches for implementation.

  • Develop a framework for cybersecurity in passenger and goods transport across all modes and provide IT connectivity that allows plug-and-play data sharing.

  • Increase data security and privacy in authentication and payment processes for mobility services (through the concepts of trustee roles, blockchain, etc.), and support the respective initiatives.

  • Employ robots, drones, and shared public transport services or logistics.

  • Multimodal navigation systems providing travellers with efficient, safe, and healthy transfer options.

  • Development of modular mobility platforms for the on-site provision of services and goods delivery.

  • Integrate cross-modal hubs and interfaces into the urban structure and connect them by harmonised infrastructure to smart sustainable corridors.

  • Provide open application programming interfaces (APIs) and user data and statistics for all modes and providers, enabling demand-oriented and demand-responsive cross-modal means of transportation.

  • Ensure accessibility of shared services and incentivise shared fleets of personal mobility devices at hubs to facilitate mode change for those with disabilities and reduced mobility.

  • Individualised mobility shells for demand-responsive transportation means.

  • Make vehicles and transportation systems more resilient by smart application of automation, connectivity, and electrification.

The roadmap for the key digital technologies in mobility are aligned with European roadmaps for terrestrial, water and aerospace transport:

  • A new European Road Transport Research Advisory Council (ERTRAC) roadmap entitled “Sustainable Energies and Powertrains for Road Transport – Towards Electrification and other Renewable Energy Carriers”.

  • Urban mobility roadmap.

  • Long-distance freight transport roadmap.

  • Towards zero logistics emissions by 2050.

  • The joint European Technology Platform (ETP) common paper published in 2019.

  • The European roadmap on connected and automated driving published in 2019.

  • The Joint Strategic Research Innovation and Deployment Agenda (SRIDA) for the AI, Data and Robotics Partnership (euROBOTICS), September 2020.

  2024 2025 2026 2027 2028 2029 2030 2031 2032 2033  
  R&D&I TTOPIC IN KEY DIGITAL TECHNOLOGIES FOR MOBILITY  
    1 - ENABLE CO2-NEUTRAL MOBILITY AND REQUIRED ENERGY TRANSFORMATION  
1.a KDT for electr. passenger cars, electrified (short range) and fuel cell trucks , electr.off.road
                       
1.b KDT for H2 fuel cell passenger cars synthetic fuelled mobility      
                       
1.c KDT for electrified airplanes, drones, ships          
                       
1.d KDT for CO2-neutral energy optimised mobility (from cradle to grave)    
                       
 
    2 - ENABLE AFFORDABLE, AUTOMATED AND CONNECTED MOBILITY FOR PASSENGERS AND FREIGHT ON ROAD, RAIL, AIR AND WATER   
2.a KDT for level 2, 2+ vehicles, remotely operated ships        
                       
2.b KDT for level 4 vehicles                
                       
2.c KDT for level 5 vehicles                
                       
 
    3 - MODULAR, SCALABLE, RE-USABLE, FLEXIBLE, CLOUD-BASED, SAFE&SECURE END-TO-END SOFTWARE PLATFORM ABLE TO MANAGE SDV MOBILITY OF THE FUTURE  
3.a CAR-OS middleware for electrified, connected level 2-3 vehicles      
                       
3.b CAR-OS middleware for electrified, connected level 4-5 vehicles and RISC 5    
                       
3.c Middleware for non-automotive electrified automated vehicles      
                       
 
  2023 2024 2025 2026 2027 2028 2029 2030 2031 2032  
  R&D&I TTOPIC IN KEY DIGITAL TECHNOLOGIES FOR MOBILITY  
    4 - PROVIDE TOOLS AND METHODS FOR VALIDATION AND CERTIFICATION OF SAFETY, SECURITY AND COMFORT OF EMBEDDED INTELLIGENCE IN MOBILITY  
4.a KDT for validation and certification for level 2+ to 4        
                       
4.b KDT for validation and certification of level 5        
                       
4.c Validation and certification of integrated mobility        
                       
 
    5 - ACHIEVE REAL-TIME DATA HANDLING FOR MULTIMODAL MOBILITY AND RELATED SERVICES  
5.a KDT for urban and long distance energy mobility systems        
                       
5.b KDT for rural energy optimised mobility systems          
                       
5.c KDT for globally energy optimised mobility systems        
                       
                       

The roadmap combines the objectives in the application research programmes 2Zero and CCAM with the derived ECS mobility challenges. The following roadmap indicates when R&D&I activities are required to ensure the key digital technologies are available for use in the different mobility domains. In areas that already include ongoing electric mobility, the focus is more on improvements to existing concepts (for example, optimisation of costs), while for others (such as electric aircrafts) it is more about focusing on lower technology readiness levels (TRLs). These are both going on in parallel and are also influencing each other.

This roadmap is a preliminary estimate in regard to when the ECS will need to be ready for the various technology fields. It will be continuously updated as new domain roadmaps become available.