Over the past six months, our Sector Insights Team – myself, Dan, and Karla, has been delving deeper into the world of Artificial Intelligence (AI). We’ve engaged with LCRIG supply chain members, councils, and national operators, and next week, I’ll be participating in a roundtable on AI. One thing is clear: AI is already transforming the transportation sector, and highways are no exception. However, it’s equally important to consider the hype surrounding AI, a term that has, at times, been overused. Cybersecurity is another crucial factor that cannot be overlooked.
As global traffic increases and cities expand, the need for efficient, safe, and sustainable highway systems becomes more urgent. AI is helping to address these challenges by improving traffic management, enhancing safety, and optimising maintenance.
AI-powered systems can use real-time data from sensors, cameras, and connected vehicles to monitor traffic and adjust signals dynamically. This reduces congestion, improves travel times, and lowers emissions. However, it raises an important policy question – should we focus on making car journeys easier, or should we prioritise encouraging more people to use public transport? This question is particularly relevant when considering the implications of devolution.
AI is also starting to enhance highway safety through advanced monitoring and predictive analytics. Computer vision technology can detect hazards like debris, broken down vehicles, and adverse weather, sending real-time alerts to drivers and traffic control centres.
In addition, AI can support autonomous vehicles through Vehicle-to-Infrastructure (V2I) communication, reducing human error, the leading cause of accidents, and making roads safer. Or will it? At a conference on Autonomy and Data in Amsterdam that I attended, concerns were raised that AI still struggles with unpredictable human behaviour on the streets. Understanding contextual nuances remains an area where humans currently outperform machines.
We know maintaining highways is complex and expensive. AI “could” simplify this by using data from smart sensors and historical records to predict when repairs or replacements are needed. While this proactive approach minimises disruptions and extends the lifespan of infrastructure, it also raises questions about budget planning and the level of predictability our public sector financial models can support.
The Road Ahead (excuse the pun)
AI is already reshaping our highways, but there is still much more to come. Emerging technologies like edge and quantum computing promise even greater advancements, paving the way for smarter, safer, and more efficient roads.
Paula Claytonsmith, CEO – errors are my own, not AI!