The ability to forecast the evolution of the traffic in a network is the basis on which many traffic management strategies and multiple ITS applications rely. Traffic simulation is increasingly able to deal with very large networks, former computational limitations no longer providing a barrierto its application in real time. Dynamic traffic management is clearly the most typical application where real time simulation offers evident advantages. In this case, the forecasting capabilities are used to compare the performances of different management strategies in response to a non-recurrent event. These scenarios are composed of a set of events - such as laneclosure, rerouting with VMS, speed limits variation or ramp metering - that can be activated manually or under detection triggers. To decrease the operational time, most of the management scenarios are already implementedin the simulation model (within a scenarios catalogue) and are activated when the performance of a particular scenario has to be assessed through simulation. The process of traffic forecasting by simulation provides largeamounts of traffic data as outputs. Thus, in order to keep the computation time reasonably low and offer the operator a synthetic view of the results, a clear definition of indicators for the scenario comparison is necessary. A real time simulation-based decision support tool is currently underimplementation in the Madrid traffic centre. The newly opened M-30 urban highway (composed of a significant number of tunnel sections) is subject to many safety considerations, and many traffic evacuation and rerouting actions may be applied in response to incidents. For this reason, a tool capable of anticipating the consequences of these actions on the neighbouringnetwork over the following critical 15 or 30 minutes is necessary to choose which set of actions on the city can support these safety measures efficiently while minimizing the impact on the rest of the traffic. For this application, the Madrid City council decided to use the AIMSUN ONLINE solution. This application is fed in real time by traffic measurement in order to be able to deduce the current traffic status on the streets and the actual demand (modelled as an origin-destination matrix). With Control plans changing dynamically during the day, AIMSUN ONLINE also reads the current control plan operated at each network intersection. M-30 safety actuationsas well as any other incident previously detected and still existing are automatically (and in some case manually) loaded into the simulation modelbefore starting the parallel simulation runs. Each simulation considers aconcrete set of actions (strategy) that might be applied in order to improve the network situation compared to the "do nothing" case. These resultsultimately allow the operator to quickly see, first, if any strategies improve the situation compared to the "do nothing" case and, if yes, which ones offer the best performance. If the suggested solution is accepted, a single validation click on the screen leads to the field application of theselected strategy. An off-line operated module allows the prediction capabilities of the simulation to be evaluated each day by comparison with real data stored during the day, offering the City Council a measure of confidence in the reliability of the system. For the covering abstract see ITRDE145999
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