WELCOME
Urban Flow is one of the models developed within the EU LDT Toolbox to help cities understand how traffic moves through their streets and where mobility problems occur.
Using real traffic observations from city detectors combined with a detailed digital representation of the road network, Urban Flow recreates vehicle movements across the city through microscopic simulation. The result is a comprehensive picture of how traffic behaves, not based on assumptions, but on observed data.
The model produces clear, practical indicators for every street segment: how many vehicles use it, how fast they travel, where congestion forms, how long queues last, and what level of emissions they generate. All results are displayed on the city map through the EU LDT Play & Visualise tool, making it easy to explore patterns and compare scenarios visually.
This enables municipalities to move from intuition-based mobility decisions to evidence-based planning, whether evaluating the impact of a street closure, comparing alternative traffic management options, or identifying where infrastructure investment would have the greatest effect.
THE CHALLENGE
Cities need to make decisions about mobility every day, such as where to restrict traffic, how to redesign intersections, whether a new bus route would reduce congestion, or where a low-emission zone would have the most impact. Yet most of these decisions are still made with limited or incomplete information.
Traffic sensors and cameras cover only a fraction of the road network. Traditional traffic studies are expensive, slow, and quickly outdated. And aggregate statistics (such as average daily traffic volumes) fail to capture how congestion builds, where queues form, or how a change in one corridor affects the rest of the network.
As a result, mobility policies are often based on partial data, professional intuition, or political pressure, rather than on a comprehensive understanding of how traffic actually behaves across the city.
Without the ability to simulate and compare alternatives before implementation, cities risk investing in interventions that underperform, create unintended side effects, or fail to address the real bottlenecks.
HOW IT WORKS
Urban Flow transforms sparse traffic observations into a full-network simulation through a multi-step process:
The simulation starts with real observations: vehicle counts recorded by city detectors at fixed intervals. Each detector provides the number of vehicles passing a specific point during a given time window. This data is the ground truth that anchors the entire simulation, the model does not invent traffic, it reconstructs it from what was actually measured.
The simulation runs on a digital representation of the city’s road infrastructure, generated from OpenStreetMap data. It includes road classifications, speed limits, lane counts, junctions, and traffic signal configurations. The quality and completeness of this network directly affect the accuracy of the simulation results.
Detectors only capture traffic at specific points, but they do not tell you where vehicles came from or where they are going. Urban Flow bridges this gap by generating a set of plausible vehicle routes across the network and then selecting the combination that best matches the observed detector counts. This produces a realistic picture of traffic across the entire city, including streets without sensors.
As the simulation runs, each vehicle’s driving behaviour (speed, acceleration, braking, idling) is used to estimate its emissions in real time. The model calculates CO₂, CO, hydrocarbons, nitrogen oxides, particulate matter, and noise for every vehicle at regular intervals. This provides a street-level environmental impact assessment directly linked to traffic conditions.
INTEGRATION WITHIN THE EU LDT TOOLBOX
Urban Flow model operates within the simulation layer of the EU LDT Toolbox, transforming traffic observations into mobility and emission outputs that can be used across tools and models.
WHY IT MATTERS
Urban Flow helps cities move from fragmented traffic data to a complete, evidence-based understanding of how mobility works across the entire road network.
See how cities make better decisions.
KEY CAPABILITIES
Models the movement of individual vehicles across the road network, including acceleration, braking, lane changes, and interactions at junctions. This level of detail captures how congestion builds and propagates — something aggregate models cannot do.
Reconstructs realistic vehicle routes from sparse detector observations using optimisation techniques. The model does not require origin-destination surveys or GPS traces — it infers plausible routes from the traffic counts alone, making it practical for cities with limited data infrastructure.
Calculates CO₂, CO, hydrocarbons, nitrogen oxides, particulate matter, and noise for each vehicle at regular intervals based on its driving behaviour. Uses the HBEFA4 emission model, providing internationally comparable results.
Supports both synchronous mode for quick, small-scale simulations and asynchronous batch mode for heavy workloads. This allows cities to run anything from a quick test on a single corridor to a full-city simulation covering hours of traffic.
All results are displayed on the city map through the EU LDT Play & Visualise tool using colour-coded layers. Traffic metrics and emission data can be explored spatially, compared across scenarios, and used to generate reports.
Cities can modify input parameters (traffic volumes, detector data, time windows) to simulate alternative conditions and compare outcomes. This supports what-if analysis for planning decisions such as street closures, rerouting, or new infrastructure.
WHO USES IT
LOOKING FOR DOCUMENTATION?
Access the right resources based on your role and what you need to achieve.
Are you a mobility planner or policy lead?
Understand how Urban Flow supports mobility planning, congestion analysis, and emission assessment.
Explore use cases and see how cities use traffic simulation to design better transport policies.
Are you part of a technical or data team?
Deploy and configure the simulation model. Prepare traffic data, set up the road network, and integrate results with Play & Visualise.
New to the Toolbox? Start with the core concepts to understand how everything connects.
STANDARDS AND COMPLIANCE
The model is mainly grounded in HBEFA4, OpenStreetMap, SDG 11, EU Green Deal, Living-in.EU, Open source reinforcing interoperability and deployment flexibility across the ecosystem.
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