Navigating to the new normal in transport led by science

There is no doubt the pandemic has severely disrupted the transport industry. All business and passenger patterns have changed in an unprecedented fashion and are continuing to change. No one can be certain as to how and when things will settle, making it clear organisations have to change how they plan and prepare for current and future travel.

One way in which this can be achieved is by taking a data driven approach. Some organisations already put data at their centre of their decision-making processes, but all businesses will now have to adopt new techniques to create insights to cope with both short and long term business priorities. With no historical precedence for the current business patterns, traditional data prediction techniques are now obsolete.

Digital twins and simulators performing 'What if' scenario modelling is fundamental for effective decision making in today's highly dynamic transport industry. It's similar to predicting the weather: the accuracy of long-term forecasts are low, while very short-term ones are high—but still not perfect. We use the weather forecast as a guide to make decisions on a day-to-day basis. Likewise, what if simulations will need to be run frequently as the business or market changes, which can be hourly or daily.

By using digital twins and advanced simulation techniques underpinned by near real-time or 'effervescent' data, transport organisations can achieve agility and accuracy in decision-making, empowering transport organisations to address key post-COVID challenges including:

• Dynamic timetable planning for public transport based on shifting patterns of critical workers, demand, and safety requirements
• Utilisation based asset maintenance to prioritise constrained resources (financial, staff, and assets) to maintain quality of service
• Capacity planning to achieve optimal day-to-day running of networks based on utilisation and changing health requirements like social distancing

These can only be addressed through comprehensive data availability and sharing across the transport value chains. Effervescent data from multiple sources can drastically improve the accuracy of what-if predictions which highlights the criticality for data sharing across transport and other adjacent industries. The future will rely on cross-industry digital transport platforms that connect multiple organisations in the value-chain.

Going beyond the operations of transport networks, digital twins and simulation can play an important role in strategic planning. Simulation can allow for the validation of business cases and benefits of capital infrastructure projects during their planning stages allowing the opportunity to adjust the plan, contingency or risk levels based on a spectrum of future scenarios.

Post-pandemic passenger patterns will be driven by changes in working arrangements of the national workforce. If hybrid-working patterns become commonplace, the nature of transport networks may have to significantly change. In this scenario, transport services will need to be demand responsive and flexible, and their planning and operations highly integrated and dynamic.

Pre-COVID-19 government priorities, like mitigating climate change and levelling up require consideration of, and action from, the transport sector. Mitigating climate change in transport through policy development will require the modelling of complex scenarios that will cover private and public transport systems. Regional development will take into account the workforce travel patterns in the region. All of which will need to be done with social equity and national prosperity in mind.

Dealing with the ever-increasing complexity that will be introduced by the circumstances outlined above will require the digital twin and simulation solutions. The level maturity of digital, AI, simulation and cloud technologies today are high, are often affordable and, in turn, can deliver value for money.

An example of such solution is Deloitte's Motion Simulator. Motion Simulator is a digital twin platform that can flexibly create 2D and 3D twins of real-world transport networks rapidly. It uses the latest virtual simulation technologies and advanced artificial intelligence to model and predict what-if scenarios. Unlike most traditional simulation tools, which are designed to handle specific scenarios, Motion Simulator is capable of answering new questions as circumstances change. This, in the post-pandemic era, where things continue to be highly dynamic, makes it a critical decision support tool for transport businesses.

The future of transport, regardless of the exact scenario and pattern it will settle into, will be complex. The transport industry can effectively handle that level complexity by adopting digital and analytical solutions that are widely available. However, many organisations whose workforces have been mainly engineering based, will have to build capability to place digital twins and simulation at the heart of operations.

Transport will remain a critical aspect in the movement of people and goods. The transport industry has the opportunity to harness the force of inevitable change brought by the pandemic with a positive outlook to address societal, economic and environmental issues that were already on the table before the pandemic. Digital twins and simulation will help them do that.

Nadun Muthukumarana is the Lead Partner in Data Analytics & Artificial Intelligence, Public sector & Transport at Deloitte LLP