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 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.

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Author:Maja KalinicGND, Jukka M. KrispORCiDGND
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/67132
Parent Title (English):Proceedings of the ICA
Publisher:Copernicus GmbH
Year of first Publication:2019
Publishing Institution:Universität Augsburg
Release Date:2020/02/13
First Page:57
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Geographie
Fakultät für Angewandte Informatik / Institut für Geographie / Professur für Angewandte Geoinformatik
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften / 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)