Floating Car Data and Fuzzy Logic for classifying congestion indexes in the city of Shanghai

In this paper, we use Floating Car Data from the city of Shanghai and Fuzzy Inference model to detect congestion indexes throughout the city. We aim to investigate to which extent traffic congestion is severe during afternoon rush hour. Additionally, we compare our results to the ones obtained by ca...

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Bibliographic Details
Published inProceedings of the ICA Vol. 2; pp. 1 - 7
Main Authors Kalinic, Maja, Krisp, Jukka M.
Format Journal Article
LanguageEnglish
Published 10.07.2019
Online AccessGet full text
ISSN2570-2092
2570-2092
DOI10.5194/ica-proc-2-57-2019

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Summary:In this paper, we use Floating Car Data from the city of Shanghai and Fuzzy Inference model to detect congestion indexes throughout the city. We aim to investigate to which extent traffic congestion is severe during afternoon rush hour. Additionally, we compare our results to the ones obtained by calculating congestion indexes on conventional way. Although we do not argue that our model is the best measure of congestion, it does allow the mechanism to combine different measures and to incorporate the uncertainty in the individual measures so that the compound picture of congestion can be reproduced.
ISSN:2570-2092
2570-2092
DOI:10.5194/ica-proc-2-57-2019