Simulate how changes in traffic flow and congestion affect collision risk likelihood. Built on sensor network data, this model enables you to evaluate how real-world traffic conditions drive risk across your road network.
Traffic risk modelling draws on data from sensor networks to model the relationship between traffic flow conditions and collision likelihood. Rather than treating risk as static, it captures how congestion, speed deviation and unexpected changes in traffic patterns contribute to elevated risk.
Using the sliders, you can simulate a range of traffic conditions (indicated by the speed of flow) at different times of day and evaluate how risk responds across the network. This can be used to help quantify the safety impact of a diversion onto roads outside their normal flow range, or identifying where and when risk concentrates during a congested period.
Each segment is scored against its own baseline, so the tool identifies where conditions are creating anomalous risk rather than simply flagging busy roads. This gives road safety teams and transport planners a reliable basis for prioritising monitoring and making the case for targeted traffic management interventions.
Interested in understanding how changing traffic flow impacts risk across your road network?