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dc.contributor.authorHatamzad, Mahshid
dc.contributor.authorPolanco Pinerez, Geanette Cleotilde
dc.contributor.authorCasselgren, Johan
dc.date.accessioned2022-09-08T08:07:21Z
dc.date.available2022-09-08T08:07:21Z
dc.date.issued2022-02-17
dc.description.abstractOne of the main challenges in developing efficient and effective winter road maintenance is to design an accurate prediction model for the road surface friction coefficient. A reliable and accurate prediction model of road surface friction coefficient can help decision support systems to significantly increase traffic safety, while saving time and cost. High dynamicity in weather and road surface conditions can lead to the presence of uncertainties in historical data extracted by sensors. To overcome this issue, this study uses an adaptive neuro-fuzzy inference system that can appropriately address uncertainty using fuzzy logic neural networks. To investigate the ability of the proposed model to predict the road surface friction coefficient, real data were measured at equal time intervals using optical sensors and road-mounted sensors. Then, the most critical features were selected based on the Pearson correlation coefficient, and the dataset was split into two independent training and test datasets. Next, the input variables were fuzzified by generating a fuzzy inference system using the fuzzy c-means clustering method. After training the model, a testing set was used to validate the trained model. The model was evaluated by means of graphical and numerical metrics. The results show that the constructed adaptive neuro-fuzzy model has an excellent ability to learn and accurately predict the road surface friction coefficient.en_US
dc.identifier.citationHatamzad, Polanco Pinerez, Casselgren. Addressing Uncertainty by Designing an Intelligent Fuzzy System to Help Decision Support Systems for Winter Road Maintenance. Safety. 2022;8(1)en_US
dc.identifier.cristinIDFRIDAID 2026535
dc.identifier.doi10.3390/safety8010014
dc.identifier.issn2313-576X
dc.identifier.urihttps://hdl.handle.net/10037/26713
dc.language.isoengen_US
dc.publisherMDPIen_US
dc.relation.journalSafety
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2022 The Author(s)en_US
dc.titleAddressing Uncertainty by Designing an Intelligent Fuzzy System to Help Decision Support Systems for Winter Road Maintenanceen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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