An Application of Dynamical System in Forecasting Motorway Traffic flow

  • Anamarija L. Mrgole University of Maribor, Faculty of Civil Engineering, Transportation Engineering and Architecture, Smetanova ulica 17, 2000 Maribor, Slovenia
Keywords: Traffic Flow, Forecasting, Dynamical System Network, Neural Network.


Circumstance is essentially too surely understood to every one of us. You're on your route, when out of nowhere you're stuck in traffic. It isn't an average "rush hour" time and ordinarily you do not worry about traffic jam. There must be a mishap or some kind of genuine accident up ahead. You slowly advance your way, heavily congested, always endeavoring to discover the blazing lights of ambulances and squad cars. At that point quickly, activity begins to move ordinarily once more. There's no sign of a mishap, episode, or whatever other reason for the slowing down in traffic. So what happened? Traffic Flow system is a human-joined, variable, open and cacheable framework. It is very nonlinear and uncertain. Under certain circumstance, disorder shows up in it. The overview of publish studies implicates the importance of finding and detecting disorders in traffic. Furthermore, the outline of procedures to recognize chaotic features - disorders in traffic flow and to forecast them demonstrates the requirement on current techniques and angle of study.


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How to Cite
L. Mrgole, A. (2017). An Application of Dynamical System in Forecasting Motorway Traffic flow. International Journal of Sciences: Basic and Applied Research (IJSBAR), 35(3), 421-429. Retrieved from