How Artificial Intelligence Can Help Prevent Vehicle Incursions on UK Roads

Vehicle incursions—where unauthorised vehicles enter restricted areas—pose a serious risk on UK roads, particularly at roadworks, temporary traffic management zones, and critical infrastructure sites.

While traditional measures like physical barriers, signage, and traffic marshals remain essential, artificial intelligence (AI) is rapidly emerging as a powerful tool to help prevent these dangerous and costly incidents.

A New Layer of Real-Time Protection

One of the most immediate benefits of AI in this context is its ability to monitor road environments in real time. AI-powered camera systems, equipped with computer vision, can detect when vehicles cross into restricted zones. Unlike conventional CCTV, these smart systems can identify incursions instantly, distinguish between authorised and unauthorised vehicles, and send alerts to control centres or on-site teams within seconds.

This allows for rapid response, potentially preventing accidents and improving the safety of both workers and road users. AI systems can also be trained to recognise near-miss behaviour—such as drivers weaving toward closed lanes—and activate digital signage to warn them before an incursion occurs.

Smarter Planning Through Predictive Analysis

Beyond real-time monitoring, AI can help road operators predict where and when incursions are most likely to occur. By analysing historical traffic patterns, weather data, site conditions, and even driver behaviour, AI models can identify high-risk periods and locations. This enables more proactive traffic management planning—such as deploying more visible signage, adjusting work schedules, or increasing personnel during peak-risk times.

For example, if past data shows that driver confusion increases during evening hours in a particular layout, that insight can inform changes to signage, lighting, or barrier placement before problems arise.

Enhancing Driver Engagement and Enforcement

AI can also support smarter communication with drivers. Integrated with variable message signs (VMS) or in-vehicle navigation systems, AI can adjust messages dynamically based on real-time traffic conditions or incursion risk. In more advanced setups, geofencing technology combined with AI can send in-car alerts to drivers approaching restricted zones, improving compliance and reducing reliance on human intervention.

When breaches do occur, AI-enhanced Automatic Number Plate Recognition (ANPR) systems can help enforce regulations by automatically capturing evidence. These systems provide timestamped video footage and detailed logs, which are useful not only for prosecution but also for improving future traffic management.

Understanding the Human Element

One of AI’s less obvious but highly valuable applications is in analysing the root causes behind vehicle incursions. By reviewing dashcam footage, telematics data, and incident reports, AI can help identify behavioural trends—such as confusion due to poorly placed signage or fatigue-related driving patterns. These insights are crucial for improving training programmes and revising operational procedures.

Building Smarter Infrastructure

Across the UK, AI is already being piloted in road safety contexts. National Highways has explored AI camera systems to detect incursions in roadworks. Transport for London has invested in machine learning tools to monitor traffic anomalies. Major infrastructure projects like HS2 are also deploying AI-assisted monitoring technologies to prevent vehicles from breaching worksite boundaries.

As these technologies mature, the integration of AI into road safety strategy will become not just a competitive advantage but a necessity.

While AI alone cannot eliminate vehicle incursions, it significantly enhances the industry’s ability to detect, predict, and prevent them. When combined with sound planning, strong enforcement, and human oversight, artificial intelligence can transform the way UK road operators protect their workers, infrastructure, and the public.

By embracing AI, the infrastructure sector has the opportunity to move from reactive safety measures to intelligent, proactive risk management—creating a safer and more efficient road network for everyone.