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impaginato corretto fullone_Layout 1 13/10/15 12.07 Pagina 1 Department of Engineering, ICT and Technologies for Energy and Transport Patent Title Title Method for traffic forecast analysis and navigation Method for traffic forecast analysis and navigation on road networks. on road networks. Ref. CNR 10366 Ref. CNR 10366 Assignee(s): IAC, Zeropiù SpA CNR Institute: IAC Main Inventor: Gabriella Bretti Countries: IT Priority date: 30/10/2014 Abstract Abstract The present invention refers to a platorm to detect traffic data moving on a road network and compute The present invention refers to a platform to detect traffic data moving on a road network and compute the state of traffic in the future. The platorm is able to receive data in standard protocols the state of traffic in the future. The platform is able to receive data in standard protocols (raw/gps/openLR etc.) once every minute at least. It is endowed with a forecasting algorithm for traffic (raw/gps/openLR etc.) once every minute at least. It is endowed with a forecasting algorithm for traffic flows that provides the traffic forecast at short or medium period (dozens of minutes) in terms of flows that provides the traffic forecast at short or medium period (dozens of minutes) in terms of average speed of cars. average speed of cars. A method for road navigation on a reference map was also developed in order to insert a path and A method for road navigation on a reference map was also developed in order to insert a path and estimate, taking into account traffic data, the convenience to take a road and, finally, to compute with a estimate, taking into account traffic data, the convenience to take a road and, finally, to compute with a routing algorithm at least one optimal path on the reference geographic map taking into account the routing algorithm at least one optimal path on the reference geographic map taking into account the cost of distance. cost of distance. Background Background Many algorithms are known to predict traffic on road networks at different times in the future, such as Many algorithms are known to predict traffic on road networks at different times in the future, such as those based on the automated analysis of historical series of traffic data of statistic probabilistic type, but those based on the automated analysis of historical series of traffic data of statistic probabilistic type, but they never use deterministic models to compute traffic through real time traffic data. they never use deterministic models to compute traffic through real time traffic data. In such a way, would be impossible to predict traffic in case of unexpected events. In such a way, would be impossible to predict traffic in case of unexpected events. Technology Technology The road network is converted in a virtual network containing important areas of traffic (“selfconsistent” The road network is converted in a virtual network containing important areas of traffic (“selfconsistent” network) and the algorithm is able to effectively apply the mathematical forecast models adopted. Traffic network) and the algorithm is able to effectively apply the mathematical forecast models adopted. Traffic data detected on the original network are projected on the virtual network and the platorm is able to data detected on the original network are projected on the virtual network and the platform is able to receive and process in real time the huge amount of data given in input to the forecast algorithm. receive and process in real time the huge amount of data given in input to the forecast algorithm. Advantages and Applicatons Advantages and Applications The invention permits to forecast traffic in the future even in case of unexpected events, such as accidents The invention permits to forecast traffic in the future even in case of unexpected events, such as accidents or strong congestions caused by bad weather. Thus we can obtain a navigation tool that is able to optimize or strong congestions caused by bad weather. Thus we can obtain a navigation tool that is able to optimize the travel time of vehicles and to reduce the fuel consumption and pollutant emissions. the travel time of vehicles and to reduce the fuel consumption and pollutant emissions. Development stage Development stage A prototype was already developed and successfully tested on a portion of the urban network in Rome. A prototype was already developed and successfully tested on a portion of the urban network in Rome. Such tool allows to create a road network composed by roads of different types, to generate simulated Such tool allows to create a road network composed by roads of different types, to generate simulated 1 data, to predict traffic and, finally, to compute travel times and, in case of congestions, to redirect traffic. data, to predict traffic and, finally, to compute travel times and, in case of congestions, to redirect traffic.