From reactive to adaptive traffic management |
If you can look further ahead, you will be better able to respond to impending traffic problems. DAT.Mobility’s short-term traffic forecasts based on real-time data are the missing link towards adaptive traffic management. They have already been used successfully in two trials: Sensor-City Assen and CHARM (PC).
The basis: data science and transport modelling
By combining data science and transport modelling, we can chart the existing traffic situation and provide a forecast for the next 5, 15 or 30 minutes even if there are incidents. The method is fast and covers the entire network based on various data sources, such as floating car data, traffic light data, Bluetooth observations, CCTV footage, and loop detection.
Supplemented by virtual patrolling
To this we add virtual patrolling which, based on these results, generates actual decision data for both road users and operators. The platform enables adaptive traffic management and is vital to Mobility as a Service (MaaS) and connected and automated vehicles.
Download paper "State Estimation, Short Term Prediction and Virtual Patrolling Providing a Consistent and Common Picture for Traffic Management and Service Providers", ITS congres Copenhagen (sept 2018)