A Scalable Approach for Short-Term Predictions of Link Traffic Flow by Online Association of Clustering Profiles

Alessandro Attanasi, Marco Pezzulla, Luca Simi, Lorenzo Meschini, Guido Gentile
2020 Transport and Telecommunication  
AbstractShort-term prediction of traffic flows is an important topic for any traffic management control room. The large availability of real-time data raises not only the expectations for high accuracy of the forecast methodology, but also the requirements for fast computing performances. The proposed approach is based on a real-time association of the latest data received from a sensor to the representative daily profile of one among the clusters that are built offline based on an historical
more » ... on an historical data set using Affinity Propagation algorithm. High scalability is achieved ignoring spatial correlations among different sensors, and for each of them an independent model is built-up. Therefore, each sensor has its own clusters of profiles with their representatives; during the short-term forecast operation the most similar representative is selected by looking at the last data received in a specified time window and the proposed forecast corresponds to the values of the cluster representative.
doi:10.2478/ttj-2020-0009 fatcat:nf5h46ppo5hsngdg5s2o47hhmu