Linlin You, Fang Zhao, L. Cheah, Kyungsoo Jeong, P. Zegras, M. Ben-Akiva
{"title":"Future Mobility Sensing: An Intelligent Mobility Data Collection and Visualization Platform","authors":"Linlin You, Fang Zhao, L. Cheah, Kyungsoo Jeong, P. Zegras, M. Ben-Akiva","doi":"10.1109/ITSC.2018.8569697","DOIUrl":null,"url":null,"abstract":"A travel data collection and visualization system, Future Mobility Sensing (FMS), has been developed to understand mobility patterns and travel behavior. FMS harnesses multi-source mobility data by collecting, fusing, and visualizing them. It consists of two components: (1) the FMS Data Collection Platform, which makes use of mobile sensing devices, such as smartphones and GPS loggers, and machine learning algorithms assisted with user verification to collect high resolution, multi-day travel data. The second component is (2) the FMS Data Fusion and Visualization Platform, which combines heterogeneous data from multiple sources to be interpreted into knowledge. This paper introduces the architecture of the FMS system and summarizes the various applications, particularly travel surveys, that it can support. Data collected in a recent commercial vehicle study in Singapore is used to demonstrate the capability of the FMS platform.","PeriodicalId":395239,"journal":{"name":"2018 21st International Conference on Intelligent Transportation Systems (ITSC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 21st International Conference on Intelligent Transportation Systems (ITSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2018.8569697","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
A travel data collection and visualization system, Future Mobility Sensing (FMS), has been developed to understand mobility patterns and travel behavior. FMS harnesses multi-source mobility data by collecting, fusing, and visualizing them. It consists of two components: (1) the FMS Data Collection Platform, which makes use of mobile sensing devices, such as smartphones and GPS loggers, and machine learning algorithms assisted with user verification to collect high resolution, multi-day travel data. The second component is (2) the FMS Data Fusion and Visualization Platform, which combines heterogeneous data from multiple sources to be interpreted into knowledge. This paper introduces the architecture of the FMS system and summarizes the various applications, particularly travel surveys, that it can support. Data collected in a recent commercial vehicle study in Singapore is used to demonstrate the capability of the FMS platform.