Rune Prytz, head of research at Stratio, on the importance of emerging technology such as AI and big data analytics in the optimisation of public transport operations.

Rune Prytz, head of research at Stratio

UK bus passenger numbers have been in precipitous decline, with figures still as low as 31% compared with pre-pandemic levels. While Covid-19 has accelerated innovation in the transport sector, with a focus on enhanced cleaning, air purification systems and even larger coaches, it has also sustained and increased car use, which poses a significant barrier to net-zero targets.

While it’s intuitive that, in order to increase passenger numbers, transport providers need to offer a service that is both affordable and reliable, there needs to be a more sustained, collective effort to understand consumer priorities when it comes to deciding whether to jump on a bus or use their own vehicle to move from A to B.

Increasing the use of public transport over private cars is key to improving the air quality in our cities and to meet climate goals by reducing the emission of harmful gas. But how can public transport operators incentivise service uptake?

Using data to transform customer experience and network efficiencies

Innovation goals in public transportation were markedly impacted by the pandemic. As a result, we saw a radical shift in priorities – from delivering fuel-efficient, greener and more reliable ways of mass transit to ensuring safer and Covid-secure commuter space. This has left us in a tenuous place, not least because of the commercial deficit facing bus companies, but also the broader strategic direction of urban infrastructure and public transport.

While there were large reductions in driving during the pandemic, UK road use and the associated levels of air pollution have since rebounded to near pre-pandemic levels. Indeed, traffic congestion in London increased by an average of 30% on its A roads since January last year.

This trend is set against the push to make a sustainable economic recovery – that is, attracting more people to use both regional and city buses. And with cars being the second largest polluter in Europe and leading driver of the gap between rich and poor urban residents, the environmental health of cities hinges on a dramatic reduction in cars.

Building a next-generation service

Solving this tension requires implementing a shared mobility strategy which leverages innovative technology to reduce consumer costs alongside transformative infrastructure changes to tackle car dominance. Public transport, and the bus in particular, must provide more journeys and carry more passengers in the years to come if we are going to tackle these issues.

Since few factors in life determine someone’s access to opportunities, getting the public back on to public transport is critical, namely, to tackle the issue of ‘transport poverty’ due to car dependency – a reality for 50% of low-income households in the UK.

Bus fare reduction schemes adopted by the Republic of Ireland and Germany are examples of how to provide relief and persuade people to switch from cars to public transport. Indeed, Germans can travel throughout the country for just €9 a month under a government scheme designed to cushion the effects of rampant inflation and higher fuel prices. But we need to reduce and sustain low costs across the board for both providers and consumers, not just in a regional context, but a global one.

The first step to this requires honing in on the meaning of ‘demand’, using data to adapt services according to consumer needs and innovate beyond the restrictions of our current systems, namely, vehicle breakdowns and poor reliability.

In practice, this means creating a more responsive public transport system where reliability is maximised and therefore trust, too. Adopting AI-based technologies like predictive fleet maintenance tools are key to accelerating a zero-breakdown reality for fleets. This approach is essential for meeting demand, providing a next-gen service that revolutionises the state of travel and fundamentally equalises the bounds of transportation.

Better data collection and analysis will allow transport providers to adapt services and deliver targeted strategies that fulfil passengers’ needs. Data will spearhead us into a transport future to be designed for the user rather than service that is provided to them. Using data, we’ll be able to understand much better what the demand is, creating a public transport service users want when they want it will be much higher. Public buses therefore require urgent innovation and data-driven analysis to extend the life-cycle of their vehicle components in the face of rising fuel costs and disrupted supply chain/shortages of materials.

Technologies like predictive fleet maintenance platforms that use AI to provide real-time, actionable insight into the internal faults of electric buses allows maintenance managers to diagnose malfunctions remotely without having to recall a vehicle off the road and physically looking into it. Utilising predictive maintenance in this process is a critical element to keep vehicles out of the workshop and on the road, enabling the service that is needed. Simply put, by pushing costs down and improving reliability, public transport providers will be able to serve more people and by extension transform the service that is being received.

Technologies such as this have never been more relevant with average UK petrol prices at 165.9p per litre in May 2022, compared with 127.2p per litre last year. Indeed, leveraging operation simulation, and data (AI) to allocate specific vehicles to routes that optimise their consumption is a way to sustain a successful fleet business.

Optimisation is gained through having full access and visibility over vehicles and will also be pivotal for EV innovation, finding gaps in statistics, in particular. Providers like Go-Ahead Ireland have benefited from such technology, with the company reporting to have extended the service to its entire fleet and expect to reduce its vehicle breakdowns by over 57% in the next three years. EV innovation and widespread adoption, in particular, hinges on manufacturing vehicles that aren’t plagued by poor battery life, for example. Through expanded visibility, a product can therefore be manufactured with data-backed assurance, spearheading optimisation and preventing downtime entirely.

The services that will shape the public transport of the future will be determined by their ability to succeed where economic pressures persist, and thrive in such circumstances, utilising data to produce a zero-downtime future for fleets. Predictive maintenance means a more reliable service that reduces congestion significantly whilst saving consumers and providers money.