Lancashire County Council – A strategic approach to deploying AI in transport

Lancashire County Council (LCC) is modernising its transport services through its Future Mobility Platform (FMP) programme, which uses technologies such as AI. LCC has a history of leadership in intelligent transport systems and was a pioneer in Urban Traffic Management Control. Now, it's upgrading its technology to meet current policies and strategies. The FMP is driven by a data-first approach and aims to shift the service from reactive to proactive, using data to tackle key challenges. The FMP supports LCC’s broader policy objectives to support local bus services and sustainable transport. The FMP architecture prioritises improvements to local bus services and supports LCC's Transforming Cities Fund (TCF), Bus Service Improvement Plan (BSIP), and Levelling Up Fund (LUF) initiatives, while also helping wider transport planning. The programme of work aims make better use of the transport network, reduce congestion, and minimise the impacts of disruptions and incidents.

This results in a challenge-led approach that ensures AI is deployed strategically and organically within the service. Developments are carefully aligned with key council strategies, including transport, digital, IT, and the corporate strategy and involve the relevant key stakeholders. The council's successful use of AI stems from a strong collaborative approach. A diverse team, drawing on expertise from across the council, fuels the service's progress. Colleagues in IT, data, and procurement provide essential knowledge and guidance, supporting the programme lead in achieving strategic objectives. The council also leverages the expertise of AtkinsRéalis, a consultancy, to gain valuable insights into the technology and AI ecosystems, ensuring well-informed decision-making in combination with the council’s professional expertise.

To achieve its data-driven goals, the service utilises machine learning and predictive analytics. These technologies, sourced from providers like VivaCity, Aimsun and Alchera, enable traffic prediction and identifying congestion hotspots.

AI technologies are integral to the Future Mobility Platform, powering several key components:

• Real-time Traffic Prediction: Aimsun's Real Time Model analyses historical traffic patterns using pattern recognition. By incorporating real-time data, the model detects anomalies, predicts future conditions, and triggers appropriate traffic management responses.
• Junction Usage Analysis: VivaCity sensors utilise computer vision and machine learning to identify various traffic entities, including vehicle types and pedestrians. This junction usage data provides valuable input to the Real Time Model.
• Congestion Hotspot Identification: The Alchera Pinch Point Analysis Tool employs pattern recognition and predictive analytics on both historical and real-time data to pinpoint network hotspots, offering actionable insights to traffic engineers. The technology has been utilised to strategically plan effective bus routes

Integrating these AI technologies within the FMP enables more data-driven transport service across the region, assisting the council’s staff in decision making.

Lancashire's Transport Strategy prioritises public transport improvements, aiming to make it the preferred travel choice through bus priority measures and service enhancements. This goal has driven the work of the transport team, particularly the Future Mobility Programme. Their approach focuses on challenges and solutions, starting with identifying service pain points. Recognising that better data would lead to more informed decisions, the team prioritised improving their service understanding through enhanced data collection and analysis. This often involved implementing new technologies, including AI tools. Thus, while technology adoption isn't explicitly mentioned in the Transport Strategy, the team has strategically leveraged it to achieve the council's broader public transport goals.

Lancashire's recently updated Digital Strategy complements the Transport Strategy by explicitly advocating for technology integration to enhance decision-making and data insights. The Future Mobility programme's approach effectively aligns with both its own service-level strategy and the council's broader digital transformation goals.

Lancashire's collaborative, cross-team working culture has enabled the transport service to deploy AI safely, responsibly, and strategically. The transport team provided the vision and direction, highlighting key transport priorities. This was complemented by close collaboration with IT colleagues, who ensured appropriate technology solutions were deployed. For example, IT cross-checked new technology requests against the council's existing systems, helping the transport team select suitable tools and ensuring alignment with the council's IT strategy.

Additionally, data specialists contributed to technology procurement, advising on tenders to strengthen the technical data aspects of AI procurement and providing expert knowledge on different technology types to address any knowledge gaps within the transport team. Finally, the procurement team facilitated the acquisition of necessary technology.

Lancashire's robust governance processes, established before the Transport service's AI deployment, are now being used to govern the application of machine learning and predictive analysis. These established processes are followed for all projects. Initially, proposed work requires approval from the Digital Design Authority (DDA), which ensures alignment with council objectives and resource availability. Subsequently, the Technical Design Authority (TDA), a body overseeing technical decisions for digital transformation initiatives, assesses the proposed approach for efficiency and effectiveness in achieving objectives. Traditional governance measures applicable to technology use, such as Data Protection Impact Assessments (DPIAs) and Equality Impact Assessments (EqIAs), are also applied to AI initiatives. These governance initiatives ensure robust internal stakeholder engagement on proposed and ongoing technology deployments, involving service leads, procurement leads, digital professionals, and senior leadership.

Building on this solid foundation, the council is developing specific governance mechanisms for AI to complement its existing approach. These include:

• an AI Working Group, integrated into the current governance model, to support officers in understanding and utilising generative AI
• development of data governance structures to address the data management challenges inherent in AI deployment
• establishment of a data steering body and appointment of a Senior Responsible Officer to coordinate and ensure alignment between the council's data strategy and data-related investments, such as training.

Lancashire County Council is implementing a robust monitoring and evaluation framework for its Intelligent Bus Priority scheme, ensuring that the technology's rollout effectively meets its strategic objectives. The Transport service is also exploring the potential of expanding its successful AI deployments to include generative AI. While current AI applications provide valuable data and information, the council aims to leverage generative AI to produce more descriptive and insightful outputs. Furthermore, the team is looking to scale its existing AI capabilities to maximise their impact, including exploring the use of predictive analytics for long-term forecasting (5-10 years).