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Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Optimizing the location of stations in bike-sharing programs: A GIS approach
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Modelling the potential effect of shared bicycles on public transport travel times in Greater Helsinki: An open data approach
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From spatial interaction data to spatial interaction information? Geovisualisation and spatial structures of migration from the 2001 UK census
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Sustainable bike-sharing systems: characteristics and commonalities across cases in urban China
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Mining bicycle sharing data for generating insights into sustainable transport systems
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Inequalities in the London bicycle sharing system revisited: impacts of extending the scheme to poorer areas but then doubling prices
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From bicycle sharing system movements to users: a typology of Vélo’v cyclists in Lyon based on large-scale behavioural dataset
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Spatio-temporal patterns of a Public Bicycle Sharing Program: the effect of weather and calendar events
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Analysing bicycle-sharing system user destination choice preferences: Chicago’s Divvy system
inferredcites →https://doi.org/10.1016/j.physrep.2009.11.002openalex-snapshot
Community detection in graphs
inferredcites →https://doi.org/10.1016/j.pmcj.2010.07.002openalex-snapshot
Urban cycles and mobility patterns: Exploring and predicting trends in a bicycle-based public transport system
inferredcites →https://doi.org/10.1016/j.socscimed.2012.01.038openalex-snapshot
Towards a differentiated understanding of active travel behaviour: Using social theory to explore everyday commuting
inferredcites →https://doi.org/10.1016/j.trc.2015.01.030openalex-snapshot
Exploring bikesharing travel time and trip chain by gender and day of the week
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Characterizing the speed and paths of shared bicycle use in Lyon
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Bike Share: A Synthesis of the Literature
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Exploring gendered cycling behaviours within a large-scale behavioural data-set
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Large-Scale Vehicle Sharing Systems: Analysis of Vélib'
inferredcites →https://doi.org/10.1103/physreve.69.026113openalex-snapshot
Finding and evaluating community structure in networks
inferredcites →https://doi.org/10.1103/physreve.70.066111openalex-snapshot
Finding community structure in very large networks
inferredcites →https://doi.org/10.1109/tvcg.2009.143openalex-snapshot
Flow Mapping and Multivariate Visualization of Large Spatial Interaction Data
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Mapping Large Spatial Flow Data with Hierarchical Clustering
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Model-Based Count Series Clustering for Bike Sharing System Usage Mining: A Case Study with the Vélib’ System of Paris
inferredcites →https://doi.org/10.14257/ijt.2013.1.1.03openalex-snapshot
Public Bikesharing and Modal Shift Behavior: A Comparative Study of Early Bikesharing Systems in North America
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Health Cobenefits and Transportation-Related Reductions in Greenhouse Gas Emissions in the San Francisco Bay Area
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Bikesharing in Europe, the Americas, and Asia
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Digital breadcrumbs: Detecting urban mobility patterns and transport mode choices from cellphone networks
What points at this work
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Bike-sharing station profiles and urban context: Understanding imbalance with asymmetry-based clustering
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Expanding Bicycle-Sharing Systems: Lessons Learnt from an Analysis of Usage
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Identifying the factors affecting bike-sharing usage and degree of satisfaction in Ningbo, China
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Determining the exact location of a public bicycle station—The optimal distance between the building entrance/exit and the station
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Human mobility in bike-sharing systems: Structure of local and non-local dynamics
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Graph convolutional network approach applied to predict hourly bike-sharing demands considering spatial, temporal, and global effects
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Implicit GPS-based bicycle route choice model using clustering methods and a LSTM network
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Computer Modelling of Temporal Networks for Bike Sharing Usage Patterns Analysis
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Travel preference of bicycle-sharing users: A multi-granularity sequential pattern mining approach
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Marked Temporal Point Processes for Trip Demand Prediction in Bike Sharing Systems
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Cluster Analysis of Stations Based on Weight SimRank in Sharing Bicycle
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Multichannel queueing behaviour in urban bicycle traffic
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DeepBike: A Deep Reinforcement Learning Based Model for Large-scale Online Bike Share Rebalancing
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Predicting Short-Term Bike-Sharing Demand at Station Level: A Deep Graph-Based Multi-Task Spatiotemporal Approach
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Predicting Short-Term Bike-Sharing Demand at Station Level: A Semi-Adaptive Graph-Based Multi-Task Spatiotemporal Approach
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TRAFFIC CONGESTION ANALYSIS WITH DIRECTIONAL STATISTICS: DESCRIPTIVE MODEL BY ANGULAR DISTRIBUTIONS FOR ROAD NETWORK AND OD DEMAND
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BIKE TO CAMPUS: SUATU GERAKAN SOSIAL BARU BERBASIS KOMUNITAS SEPEDA
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Accesibilidad universal e inclusión social en la implementación del programa MiBici en Guadalajara, 2014-2019
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EXPLORING THE LINK BETWEEN TRAVEL BEHAVIOUR AND SUSTAINABLE MOBILITY
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Understanding the Utilization Characteristics of Bicycle-Sharing Systems in Underdeveloped Cities: A Case Study in Xuchang City, China
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A General Cooperative Optimization Approach for Distributing Service Points in Mobility Applications
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Literature Review on Behavioral Analysis of Bike Use and Decision Support Methods for Soft Mobility Infrastructure and Service Development
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Machine Learning Models for Bike-Sharing Demand Forecasting
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Machine Learning Approaches to Bike-Sharing Systems: A Systematic Literature Review
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Spatial and Temporal Characteristic Analysis of Imbalance Usage in the Hangzhou Public Bicycle System
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Using Object Detection on Social Media Images for Urban Bicycle Infrastructure Planning: A Case Study of Dresden
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Construction and Analysis of Space–Time Paths for Moving Polygon Objects Based on Time Geography: A Case Study of Crime Events in the City of London
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Spatio-Temporal Behavior Analysis and Pheromone-Based Fusion Model for Big Trace Data
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A Visual Analysis Approach for Inferring Personal Job and Housing Locations Based on Public Bicycle Data
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Heuristic Bike Optimization Algorithm to Improve Usage Efficiency of the Station-Free Bike Sharing System in Shenzhen, China
inferred← citeshttps://doi.org/10.3390/ijgi8060281openalex-snapshot
Weighted Dynamic Time Warping for Grid-Based Travel-Demand-Pattern Clustering: Case Study of Beijing Bicycle-Sharing System
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Analysis of the Cycling Flow Between Origin and Destination for Dockless Shared Bicycles Based on Singular Value Decomposition
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Attitudes and Motivation to Use Public or Individual Transport: A Case Study of Two Middle-Sized Cities
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Analysis of Spatial and Temporal Characteristics of Citizens’ Mobility Based on E-Bike GPS Trajectory Data in Tengzhou City, China
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Analysis of Network Structure of Urban Bike-Sharing System: A Case Study Based on Real-Time Data of a Public Bicycle System
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Spatiotemporal Characteristics of Bike-Sharing Usage around Rail Transit Stations: Evidence from Beijing, China
inferred← citeshttps://doi.org/10.3390/su13010141openalex-snapshot
Policy Zoning for Efficient Land Utilization Based on Spatio-Temporal Integration between the Bicycle-Sharing Service and the Metro Transit
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Enhancing Sustainable Transportation: AI-Driven Bike Demand Forecasting in Smart Cities
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Electric Bikes and Scooters Versus Muscular Bikes in Free-Floating Shared Services: Reconstructing Trips with GPS Data from Florence and Bologna, Italy
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Spatio-Temporal Graphs in Transportation: Challenges, Optimization, and Prospects
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Multi-scale and Interactive Visual Analysis of Public Bicycle System
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Bike-sharing usage : mining on the trip data of bike-sharing users
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Bike-sharing mobility patterns: a data-driven analysis for the city of Lisbon
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Practical method to improve usage efficiency of bike‐sharing systems
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A Comprehensive Framework for Dynamic Bike Rebalancing in a Large Bike Sharing Network
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Intertemporal Community Detection in Human Mobility Networks
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Predicting Station-Level Bike-Sharing Demands Using Graph Convolutional Neural Network
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Towards Dynamic Urban Bike Usage Prediction for Station Network Reconfiguration
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Revealing social dimensions of urban mobility with big data: A timely dialogue
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Spatio-temporal analysis of the covid-19 impacts on the using Chicago urban shared bicycles by tensor-based approach
inferred← citeshttps://doi.org/10.60093/jiciviltech.1565857openalex-snapshot
Application of Hierarchical Clustering Algorithm to Classify Docked Bike-Sharing System Stations
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Big data-driven optimization in transportation and communication networks
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Spatio-Temporal Patterns of a Public Bike Sharing System in Seoul - Focusing on Yeouido District -
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