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Predicting traffic flow with machine learning

Noorlander, M.S. (2021) Predicting traffic flow with machine learning.

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Abstract:This work describes a way of predicting traffic flow with machine learning. To accomplish this goal, several research questions have been created. These are Q1: What machine learning techniques can be used to accurately predict traffic flow? Q2: How can we use the predicted traffic flow to avoid congestion? Q3: What is the influence of non-cooperative vehicles on this model? The first question will be used to select the most accurate technique from an LSTM, GRU or CNN. The technique can be used to create a rerouting mechanism in SUMO to prevent congestion. Finally the work describes ways to evaluate the effect of non-cooperative vehicles on the rerouting mechanism to test the effectiveness on a more realistic scenario.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Computer Science BSc (56964)
Link to this item:http://purl.utwente.nl/essays/85689
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