Open AccessTraffic flow prediction model and probability of congestion
Author(s) -
Marcelo Pilamunga-Poveda,
J. M. Lavin,
M. Aldás Sánchez,
David Rı́os Insua
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/844/1/012008
Subject(s) - traffic congestion , computer science , risk analysis (engineering) , moment (physics) , investment (military) , operations research , transport engineering , work (physics) , traffic flow (computer networking) , quality (philosophy) , business , engineering , computer security , mechanical engineering , physics , classical mechanics , politics , law , political science , philosophy , epistemology
Investment in the management of integrated activities for better community development determines the progress of a city. Generate actions directed to change and evolution can promote greater satisfaction among its inhabitants. One of those activities is the one concerning transit, which is one of the most transcendental factors in the quality of life of a modern city. Thus, good road planning is of vital importance for their development. To do this, studies must be conducted that allow us to have a diagnosis of reality and thus make decisions would help to minimize or avoid problems that are occurring or that may appear in the future. However, to make a study of this type whenever it is required is expensive in terms of time and resources. This work proposes a model that allows predictions of traffic flows in different relevant sections of a city and, predict issues such as traffic saturation in them, thus determining possible solutions to road congestion, it can be presented at a given moment. These possible alternative solutions could consequently would reduce costs in time, fuel, pollution among others.