Pseudo Real-Time Traffic Forecasting
A Pseudo Real-Time Traffic Forecasting System for the A4 Milano-Torino Motorway
In response to Italy’s 2018 “Smart Road” initiative, a team of experts from citiEU Consultancy, Polinomia Srl, and Bentley Systems developed a pseudo real-time traffic model for the A4 Milano-Torino motorway. Using the OpenPaths DYNAMEQ software, the project aimed to provide 15- to 45-minute rolling traffic forecasts by integrating real-time data with analytical modelling. The model combines both toll and non-toll motorway sections using two primary data sources: Daily Analytical Flows data for tolled segments and TomTom Origin-Destination (OD) data for the non-tolled section. This dual-data approach allowed for the construction of detailed demand matrices, capturing temporal and vehicle-type variability across 11 consistent time periods and 7 typical days.
The model was embedded in SINELEC’s ‘SINCRO’ platform, enabling dynamic traffic assignment (DTA) updates in near real-time. Events such as lane closures, weather incidents, and construction works were incorporated through a scenario management interface, calibrated with historic TomTom traffic data. The simulation outputs include queue lengths, traffic conditions, and optimal speed advisories to mitigate network congestion. The model's ability to rapidly simulate scenarios with high reliability and integrate big data inputs made it an effective tool for both operational planning and emergency response.
Ultimately, this implementation provided motorway operators with a powerful decision-support system that met legal requirements and improved roadway resilience. The strong Python integration allowed rapid scenario development, while continuous updates and calibrations ensure robust forecasting accuracy. The case showcases how high-performance traffic modelling and data fusion can support smarter, safer, and more efficient transport infrastructure.
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