Using AI to Deliver Smarter Bus Priority at Abbey Bridge Junction, Worcester

Solution

To meet this need, Worcestershire County Council deployed Clearview Intelligence’s Insight Vision AI multi-modal sensors at Abbey Bridge Junction. These sensors use advanced machine-learning and computer vision to detect, classify and track different road users in real time, including buses, general traffic, cyclists and pedestrians.

The system was configured to establish journey-time spans on each junction approach, enabling the Council to measure how long vehicles, and particularly buses, took to traverse the corridor. Specialised bus detection and occupancy zones were created to identify when a bus was approaching the junction and to estimate passenger demand. This allowed the team to quantify how often priority “hurry calls” could be issued to the traffic controller and to test logic that would adjust signal behaviour dynamically in response to
actual demand.

All captured data is securely hosted within the Insight platform, which integrates vision analytics, floating vehicle data, and signal performance metrics into a single, dataagnostic environment. This creates a consistent, auditable, and defendable evidence base, ensuring that investment decisions and policy development are grounded in robust, transparent data.

The Challenges

• Abbey Bridge Junction is a busy four-arm signalised junction located on a key bus corridor. Each approach serves journey-time spans of approximately 800m to 1.2km, carrying a complex mix of buses, private vehicles, pedestrians and cyclists
• Historically, bus delays at the junction could be caused by a variety of factors, including signal delay, congestion, passenger boarding time, and general traffic pressure. Without high-quality, classified movement data, it was difficult to separate true congestion delay from normal operational dwell time, limiting the Council’s ability to design targeted, effective interventions.
• The Council needed a solution capable of capturing highly accurate, multi-modal movement data, understanding network occupancy by classification and demand, and feeding this intelligence into a system that could dynamically influence signal timings based on real-world conditions.

Conclusion

The Abbey Bridge Junction PoC demonstrates a practical, low-risk pathway to delivering data-driven bus priority. By combining AI-powered vision sensing with dynamic signal optimisation, Worcestershire County Council is building a scalable, evidence-based approach to improving bus reliability while safeguarding overall network performance.