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

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.

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