Eine Bestimmung der Oberflächenqualität von Fahrradinfrastruktur durch Smartphone-Beschleunigungsdaten mithilfe des k-means++-Algorithmus / Determination of the Surface Quality of the Bicycle Infrastructure by Smartphone Acceleration Data Using the k-means++ Algorithm
{"title":"Eine Bestimmung der Oberflächenqualität von Fahrradinfrastruktur durch Smartphone-Beschleunigungsdaten mithilfe des k-means++-Algorithmus / Determination of the Surface Quality of the Bicycle Infrastructure by Smartphone Acceleration Data Using the k-means++ Algorithm","authors":"Stefan Kranzinger, S. Leitinger","doi":"10.14627/537707013","DOIUrl":null,"url":null,"abstract":"Providing a well-maintained cycling infrastructure has a positive impact on the comfort and safety of cycling in road traffic and creates the conditions for its acceptance as an alternative to private or public transport. This study uses data from smartphone accelerometers and a k-means++ algorithm to determine the quality of road sections. This is easy and cost-effective to apply to large-scale cycling networks and shows in a case study for the city of Salzburg that poorly passable lane sections can be well localised and subsequently maintained in a targeted manner.","PeriodicalId":36308,"journal":{"name":"AGIT- Journal fur Angewandte Geoinformatik","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AGIT- Journal fur Angewandte Geoinformatik","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14627/537707013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Providing a well-maintained cycling infrastructure has a positive impact on the comfort and safety of cycling in road traffic and creates the conditions for its acceptance as an alternative to private or public transport. This study uses data from smartphone accelerometers and a k-means++ algorithm to determine the quality of road sections. This is easy and cost-effective to apply to large-scale cycling networks and shows in a case study for the city of Salzburg that poorly passable lane sections can be well localised and subsequently maintained in a targeted manner.