Using Mobile Phones to Crowd-source User Flow Data for Assessing Bike Sharing Site Suitability

S. Wu, Luo Wei Lun, Ju-Ying Chan, LiChuan Yang, Irene Wan, H. Lin
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引用次数: 7

Abstract

This paper presents a novel phone app for use in the collection of flow data pertaining to users approaching and leaving a station before and after using a shared bike. Two novel functions were incorporated in the app to motivate adoption. One “Bike Station Querying” function is a search program indicating the location of nearby rental stations and the current availability of bikes. The other “Staged Route Planning” function is a route planning based on when the user would like to pick up and park the bike. Even while riding a bike, the user can alter their destination simply by pressing a button or muting the voice routing instructions. The collection of data in the background consumes very little power thanks to an algorithm designed to limit energy consumption. Data is uploaded to a cloud-based server for analysis by the operators or planners of bike sharing stations.
利用手机众包用户流量数据评估共享单车站点适宜性
本文提出了一种新颖的手机应用程序,用于收集用户在使用共享单车前后进出车站的流量数据。应用程序中加入了两个新颖的功能来激励采用。其中一个“自行车站查询”功能是一个搜索程序,显示附近的租赁站的位置和当前的自行车可用性。另一个“分段路线规划”功能是基于用户何时取车和停放自行车的路线规划。即使在骑自行车时,用户也可以通过按下按钮或将语音路由指令静音来改变目的地。由于设计了一种限制能耗的算法,在后台收集数据消耗的能量非常少。数据被上传到基于云的服务器上,供共享单车站的运营商或规划者分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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