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Digital Roads of the Future


Engineers have a history of collecting data from the physical infrastructure, using it to design alternative interventions to engineering problems, and applying the theoretically best intervention back to the infrastructure since the advent of engineering drawings. This loop is still true to this day. However, our ability to collect data, model it, and apply interventions has grown exponentially and become increasingly automated. Technological advances have reached the maturity and potential to (a) capture physical infrastructure (i.e. physical twin) data and transmit it to the asset’s digital copy, i.e., its digital twin; (b) structure, generate, update, curate and communicate with the digital twin; and (c) leverage the digital twin to monitor asset performance and plan interventions that are more sophisticated than ever before.

We aim to enable Digital Twins as a resilient data backbone for highway infrastructure through the Digital Roads of the Future initiative. The key considerations underpinning our thinking are:

Understanding what exactly is a Digital Twin in this context and how should it be designed. At a fundamental level, we need to derive (i) proof-of-concept data structures and cloud architectures able to support highway product data built with smart materials, and to enable data science, robotic monitoring and federation across multiple cloud tenants.

Understanding how should a Digital Twin be constructed, maintained and operated. We need methods to generate and update the Digital Twins from pre-existing, field-captured and smart materials-provided data. We also need to devise a strategy for static and dynamic information curation to enable productisation and facilitate information security and future-proofing.

Understanding how to maximise value gain from Digital Twins for human operators and machines alike. We need to design and implement machine-information and human-information interfaces to support data science and automation processes.

The Digital Twins theme acts as the main reference point for all other themes of this initiative and the foundation for an initiative-wide platform and interfaces needed to bring the initiative’s outcomes to market. It is a core business advantage for the initiative’s industry partners, and its outcomes will be designed to be extensible to other asset types. It will also help develop industry partners gain an understanding on the purpose and scope of future uses of a digital twin.

The key digitial twin “challenges” are outlined below. 

What are potential business cases for Highway Digital Twins?

As digital twins move from being an experimental concept to a core part of our organisations and societies, it becomes increasingly important to be able to identify ROI and attach value to them. However, to realise these values, it is essential to see digital twinning as a transformation: people, processes and technology must be brought together holistically. Moreover, there are numerous hurdles to overcome before this transformation pays off. Therefore, the question arises as to which new business models are needed for the sustainable management of a digital twin. Potential challenges are:

- What are potential clients for a Digital Twin?
- Why should someone invest in Digital Twins?
- What is the return of investment for a Digital Twin?
- How to combine businesses (top-down) and technology (bottom-up)?
- How to quantify the economic benefits of Digital Twins?
- What are suitable financial and business models for Digital Twins?
- Who owns the Digital Twin, Data, Models, etc.?

Industry Sponsor: TRL

How can we build a trustworthy Digital Twin?

Digital Twins represent the beginning of a new digital era. With the help of Digital Twin technologies, data is not only collected and analysed automatically, but the insights gained are used to control the Physical Twin optimally. To achieve this, novel AI and ML algorithms are being deployed. However, the infrastructure operator is faced with the difficult question of how much trust he can place in the proposed results from the Digital Twin. Frequently, these decisions are associated with high financial costs and, in the worst case, it is a matter of life and death. Accordingly, decisions must be understandable and trustworthy. Which leads to the question, how we can create a trustworthy Digital Twin? Potential challenges are:

- How can we trust the analysis and results of a Digital Twin?
- How can the results of a Digital Twin be used?
- Are provided options and benefits clear?
- How to deal with incomplete data?

Industry Sponsor: Atkins, OS

How can a Highway Digital Twin evolve over time?

The lifespan of infrastructure systems usually extends over several decades. During this period, they must reliably provide the corresponding service. In contrast, digital technology is subject to rapid changes. Technologies that are state-of-the-art today may be obsolete in just a few years. In this area of tension between long-lived infrastructure systems and the rapid development of technology, the question arises of how to design a reliable digital twin that lasts over the lifetime of the infrastructure. This also includes incorporating existing solutions into the design of the Digital Twin to make it backwards compatible. Potential challenges are:

- How to future-proof Digital Twins?
- How to ensure backwards compatibility?
- How to integrate "old" technologies into a Digital Twin environment?
- How to deploy a Digital Twin into an existing workflow?
- How can a Digital Twin be integrated within existing Software.

Industry Sponsor: OS

What are the minimum data requirements for a valuable Digital Twin?

The idea of a digital twin is based on analysing data from the real world and deriving appropriate courses of action. This means that a certain amount of data with the corresponding quality forms the basis of a digital twin. So the question is, what are the minimum data requirements of a Digital Twin. Or in other words, what is the Minimum Viable Product (MVP) of a Digital Twin, which has enough features to attract early adopter customers and validate a product idea early in the product development cycle. Potential challenges are:

- What are unique (data) requirements for Highway Digital Twins?
- What data can be shared between different infrastructures Digital Twins (e.g. supply infrastructure)?
- What are the standards for Digital Twins?
- How to harmonise different Digital Twins?
- How to integrate other data sources (e.g. railway, weather, environment data)?

Industry Sponsor: OS

Contact for Digital Twin Theme

Potential applicants should contact the smart materials theme lead, Professor Ioannis Brilakis (, for any queries regarding these challenges.

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