Incidents and emergency events in passenger rail transport are more frequent than expected. One of the top priorities is to minimize the consequences of this type of event by ensuring the safety of passengers. This responsibility often falls on people who have to make decisions quickly and efficiently. To achieve this goal there are predefined plans that establish an orderly sequence of actions where it has been proven to be ineffective and insufficient. The objective of SIGNAL was to develop and test an intelligent management system prototype capable of supporting decision makers and managers in front of incidents and emergencies in commuter trains.
SIGNAL will be able to offer decisions, actions and suggestions in real time, mainly oriented to guarantee the safety and support for passengers, based on the analysis of multiple alternatives with advanced computational modeling and simulation techniques and the use of artificial intelligence methods , expert systems and decision trees. This will allow the decision-maker to take scientific-based measures, reduce decision cycles, and thus increase effectiveness in resolving the event.