{"title":"利用大数据估算电动滑板车交通流量以支持微交通规划","authors":"Chen Feng, J. Jiao, Haofeng Wang","doi":"10.1080/10630732.2020.1843384","DOIUrl":null,"url":null,"abstract":"ABSTRACT Dockless e-scooter sharing, as a new shared micromobility service, has quickly gained popularity in recent years. In this paper, we present a practical approach to estimating e-scooter flow patterns without knowing the actual routes taken by the e-scooter riders. Our method takes advantage of a huge open dataset that contains the origins and destinations of millions of trips. We show that our models can help cities better support the emerging shared micromobility service. The additional information generated in the modeling process can also be useful for a more refined analysis of e-scooter trips.","PeriodicalId":47593,"journal":{"name":"Journal of Urban Technology","volume":"9 1","pages":"139 - 157"},"PeriodicalIF":4.6000,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"Estimating E-Scooter Traffic Flow Using Big Data to Support Planning for Micromobility\",\"authors\":\"Chen Feng, J. Jiao, Haofeng Wang\",\"doi\":\"10.1080/10630732.2020.1843384\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Dockless e-scooter sharing, as a new shared micromobility service, has quickly gained popularity in recent years. In this paper, we present a practical approach to estimating e-scooter flow patterns without knowing the actual routes taken by the e-scooter riders. Our method takes advantage of a huge open dataset that contains the origins and destinations of millions of trips. We show that our models can help cities better support the emerging shared micromobility service. The additional information generated in the modeling process can also be useful for a more refined analysis of e-scooter trips.\",\"PeriodicalId\":47593,\"journal\":{\"name\":\"Journal of Urban Technology\",\"volume\":\"9 1\",\"pages\":\"139 - 157\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2020-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Urban Technology\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1080/10630732.2020.1843384\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"URBAN STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Urban Technology","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1080/10630732.2020.1843384","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"URBAN STUDIES","Score":null,"Total":0}
Estimating E-Scooter Traffic Flow Using Big Data to Support Planning for Micromobility
ABSTRACT Dockless e-scooter sharing, as a new shared micromobility service, has quickly gained popularity in recent years. In this paper, we present a practical approach to estimating e-scooter flow patterns without knowing the actual routes taken by the e-scooter riders. Our method takes advantage of a huge open dataset that contains the origins and destinations of millions of trips. We show that our models can help cities better support the emerging shared micromobility service. The additional information generated in the modeling process can also be useful for a more refined analysis of e-scooter trips.
期刊介绍:
The Journal of Urban Technology publishes articles that review and analyze developments in urban technologies as well as articles that study the history and the political, economic, environmental, social, esthetic, and ethical effects of those technologies. The goal of the journal is, through education and discussion, to maximize the positive and minimize the adverse effects of technology on cities. The journal"s mission is to open a conversation between specialists and non-specialists (or among practitioners of different specialities) and is designed for both scholars and a general audience whose businesses, occupations, professions, or studies require that they become aware of the effects of new technologies on urban environments.