AI readiness in the transport sector

The industry is siloed, leading to a fragmented landscape where the lack of unified standards impedes AI integration across systems

AI is creeping into a wide range of transport-related tools, services and procedures. But is the sector ready? The government has been busy with preparation for AI, with much happening in the space for public sector, transport operator and supply chain AI-readiness. As the Department for Transport (DfT) works on its forthcoming Transport AI Strategy and AI Strategy Action Areas, much work has gone into identifying challenges to AI adoption. 

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The transport, logistics and warehousing sector in the UK has struggled to adopt AI. There are divergent opinions, fragmented ecosystems, policy, politics and regulation at play. But we also have the right fundamentals for transformative change with the use of AI and machine learning technologies,” says the 2023-2024 Innovate UK Bridge AI programme’s annual report. 

It adds: “Parts of the sector are still learning how to leverage value out of more basic digital ways of working – let alone using AI. But there are forms of AI that hold the most near-term promise for the sector. Firstly, the use of machine learning models to support quantitative analytics, unlocking insights in complex system design and operation, from dynamic logistics re-routing optimisation to stock and crew balancing. Secondly, the (measured) use of LLMs to support human-understandable engagement with, and presentation of, mobility information to communicate complex scenarios to diverse audiences, whether a journey planner or a summary report.

By and large, suggests Bridge AI, the type of AI being deployed is not the core of the adoption challenge: instead, a multitude of barriers exist ranging from dynamics around industry culture, skills in the workforce, ethics and security, perception of AI, procurement and funding models, data governance and standards. None of these issues are new, and documents ranging from the Transport Data Strategy all the way to more recent technical work done by Digital Catapult’s AI adoption toolkit have laid out sensible ideas to address and minimise these challenges.

To drive the biggest impact, the key challenges blocking AI adoption in transport are procurement and funding models, AI perception (from users to those who hold the budgets), and skills of those purchasing, designing and using AI-driven tools safely and effectively. 

“Early signs of success will become evident with the communication of more case studies and an uptick in cross-transport-sector communication. AI adoption in transport is coming, but it will take a big effort in public and private alignment to unlock the real value,” says the report.

Much work has gone into identifying challenges to AI adoption and putting in place measures to drive adoption forward.  This week, for example,  has seen the launch of the DfT’s Enhancing Passenger Experience – AI in Transport Competition. 

In collaboration with Connected Places Catapult, this competition “recognises the transformative potential AI in shaping the future of the UK’s transport system” and asks SMEs to submit a use case proposal for an AI-driven transport solution that complements government objectives.

Use cases taking shape

Meanwhile, use cases for local authorities are taking shape. In Greater Manchester, more than 3,200 people were captured on camera recently using mobile phones while driving, or not wearing seat belts, during a five-week trial using AI, demonstrating the potential of AI in the road safety sector. 

VivaCity has been working with Oxfordshire County Council to use AI computer vision sensors to detect near miss incidents on their roads. VivaCity quantifies near misses, analysing the trajectories of road users in time and space, and how they relate to each other – without the need for manual analysis. Between 12 December 2022 and 12 February 2023, VivaCity recorded 1,132 near miss events between cyclists and motorised vehicles.

But there is more to do. The industry is also siloed, says the 2023-2024 Innovate UK Bridge AI programme’s annual report, with each mode of transport (rail, road, air, or sea) having developed its own set of operational protocols and systems. “This has led to a fragmented landscape where the lack of unified standards impedes AI integration across different systems. 

“Discrepancies in data formats, communication protocols and operational procedures mean that AI protocols that are designed for one system may not function correctly, or at all, when applied to another.”

Data innovation

Data innovation is a key part of AI development. Back in November 2022, the Alan Turing Institute began a partnership with the Geospatial Commission to develop a decision support tool focused on spatial modelling for land use. The initial project explored how data science and AI could be used to support land use decision making, in collaboration with Newcastle City Council planners. The result was a prototype tool, DemoLand, which could suggest land use scenarios that would lead to desired outcomes. The Geospatial Commission and the Turing Institute extended its partnership to further develop DemoLand by introducing geospatial AI – a tool that will supply actionable insights from a wide range of data sources in time for the Government’s ambitious plans to reform the National Planning Policy Framework (NPPF). 

This major spatial planning reset requires that planners have access to accurate detailed data about land available for the many competing uses required of it: transport networks, civic buildings and amenities, housing, agricultural land, energy, floodplains, waste disposal and green and blues spaces being some of the most obvious. 

Public trust in AI is also critical to its uptake, and the Government has updated its Responsible AI Toolkit – a toolkit for practitioners to support the responsible use of AI systems – and has issued a new report on Assuring a Responsible Future for AI.  

Responsible AI UK, an international ecosystem for responsible AI research and innovation, funded by the Technology Missions Fund, has released its first annual report. It says: "The AI landscape is changing rapidly, with new challenges emerging in a range of sectors, within government, industry and for society. RAi UK aims to be the trusted voice that they turn to for advice on how to develop and integrate AI into their processes, products, and daily lives to ensure AI is responsibly deployed and governed.”

However, inevitably there are challenges on the route to AI adoption. The Ada Lovelace Institute (Ada) has called for the creation of a national taskforce to support the procurement of AI technology in local government.

It made the recommendation in a recent report on the issue, Spending Wisely, based on its research into how procurement of AI is working in the sector. This is the second report in Ada's Procurement of AI and data-driven systems in local government project, and is an area that will given special focus at the Transport AI 2025 event, to be held in Manchester on 5 February.

 

 

 

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