Karlson Hargroves, Daena Ho, Daniel Conley, Peter Newman
{"title":"How Can “Big Data” Be Harnessed to Enhance Congestion Management","authors":"Karlson Hargroves, Daena Ho, Daniel Conley, Peter Newman","doi":"10.11648/J.IJTET.20210703.11","DOIUrl":null,"url":null,"abstract":"Traffic congestion is a key issue facing transport planners and managers around the world with many now asking if there are any promising technologies offering new solutions. In the US, the cost of congestion was $121 billion in 2012 and in 2015 alone Australia’s capital cities were estimated to have a combined congestion cost of $16 billion, expected increase to $37 billion by 2030. With the rapidly growing availability of data and the ability to analyse large data sets this paper investigates the question “What role can 'Big Data' play to assist with congestion management?” There is great interest and hype around 'Big Data' and this paper provides a summary of an investigation into its value to assist in relieving congestion. The paper explores the emerging types of large data sets, considers how data will be sourced and shared by vehicles and transport infrastructure in the future, ad explores some of the associated challenges. Despite the opportunities of Big Data not being fully realised it is already clear that it presents a significant tool for transport planners and managers around the world to assist in managing congestion. The research is based on research undertaken with the Sustainable Built Environment National Research Centre (SBEnrc).","PeriodicalId":265375,"journal":{"name":"International Journal of Transportation Engineering and Technology","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Transportation Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/J.IJTET.20210703.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Traffic congestion is a key issue facing transport planners and managers around the world with many now asking if there are any promising technologies offering new solutions. In the US, the cost of congestion was $121 billion in 2012 and in 2015 alone Australia’s capital cities were estimated to have a combined congestion cost of $16 billion, expected increase to $37 billion by 2030. With the rapidly growing availability of data and the ability to analyse large data sets this paper investigates the question “What role can 'Big Data' play to assist with congestion management?” There is great interest and hype around 'Big Data' and this paper provides a summary of an investigation into its value to assist in relieving congestion. The paper explores the emerging types of large data sets, considers how data will be sourced and shared by vehicles and transport infrastructure in the future, ad explores some of the associated challenges. Despite the opportunities of Big Data not being fully realised it is already clear that it presents a significant tool for transport planners and managers around the world to assist in managing congestion. The research is based on research undertaken with the Sustainable Built Environment National Research Centre (SBEnrc).