Bicycle Sharing, Bicycle Commuting, Bike Sharing

Chapter Contents (Back)
Shared Ride Systems. Bicycle Sharing.

Pfrommer, J., Warrington, J., Schildbach, G., Morari, M.,
Dynamic Vehicle Redistribution and Online Price Incentives in Shared Mobility Systems,
ITS(15), No. 4, August 2014, pp. 1567-1578.
bicycles BibRef

Leu, J.S.[Jenq-Shiou], Zhu, Z.Y.[Zhe-Yi],
Regression-based parking space availability prediction for the Ubike system,
IET-ITS(9), No. 3, 2015, pp. 323-332.
DOI Link 1506
bicycles BibRef

Corno, M., Berretta, D., Savaresi, S.M.,
An IMU-Driven Rider-on-Saddle Detection System for Electric-Power-Assisted Bicycles,
ITS(17), No. 11, November 2016, pp. 3184-3193.
Bicycles BibRef

Kiefer, C., Behrendt, F.,
Smart e-bike monitoring system: real-time open source and open hardware GPS assistance and sensor data for electrically-assisted bicycles,
IET-ITS(10), No. 2, 2016, pp. 79-88.
DOI Link 1602
Global Positioning System BibRef

Schweizer, J., Bernardi, S., Rupi, F.,
Map-matching algorithm applied to bicycle global positioning system traces in Bologna,
IET-ITS(10), No. 4, 2016, pp. 244-250.
DOI Link 1606
Global Positioning System BibRef

Schlote, A., Chen, B., Shorten, R.,
On Closed-Loop Bicycle Availability Prediction,
ITS(16), No. 3, June 2015, pp. 1449-1455.
Availability BibRef

Lopez, A.J.[Angel J.], Astegiano, P.[Paola], Gautama, S.[Sidharta], Ochoa, D.[Daniel], Tampčre, C.M.J.[Chris M. J.], Beckx, C.[Carolien],
Unveiling E-Bike Potential for Commuting Trips from GPS Traces,
IJGI(6), No. 7, 2017, pp. xx-yy.
DOI Link 1708

Hrncír, J., Žilecký, P., Song, Q., Jakob, M.,
Practical Multicriteria Urban Bicycle Routing,
ITS(18), No. 3, March 2017, pp. 493-504.
Approximation algorithms BibRef

Liu, D.X.[Dong-Xu], Dong, H.Z.[Hong-Zhao], Li, T.B.[Tie-Bei], Corcoran, J.[Jonathan], Ji, S.M.[Shi-Ming],
Vehicle scheduling approach and its practice to optimise public bicycle redistribution in Hangzhou,
IET-ITS(12), No. 8, October 2018, pp. 976-985.
DOI Link 1809

Mao, D.H.[Dian-Hui], Hao, Z.H.[Zhi-Hao], Wang, Y.[Yalei], Fu, S.T.[Shu-Ting],
A Novel Dynamic Dispatching Method for Bicycle-Sharing System,
IJGI(8), No. 3, 2019, pp. xx-yy.
DOI Link 1903

Pajarito, D.[Diego], Gould, M.[Michael],
Mapping Frictions Inhibiting Bicycle Commuting,
IJGI(7), No. 10, 2018, pp. xx-yy.
DOI Link 1811

Tang, G., Keshav, S., Golab, L., Wu, K.,
Bikeshare Pool Sizing for Bike-and-Ride Multimodal Transit,
ITS(19), No. 7, July 2018, pp. 2279-2289.
Bicycles, Employment, Public transportation, Rail transportation, Schedules, Sociology, Statistics, Bikeshare pool sizing, multimodal transit BibRef

He, B.[Biao], Zhang, Y.[Yan], Chen, Y.[Yu], Gu, Z.H.[Zhi-Hui],
A Simple Line Clustering Method for Spatial Analysis with Origin-Destination Data and Its Application to Bike-Sharing Movement Data,
IJGI(7), No. 6, 2018, pp. xx-yy.
DOI Link 1806

Jing, W.P.[Wei-Peng], Kang, J.[Jian], Liu, M.L.[Mei-Ling],
Mining taxi trajectories for most suitable stations of sharing bikes to ease traffic congestion,
IET-ITS(12), No. 7, September 2018, pp. 586-593.
DOI Link 1808

Pritchard, R.[Ray], Frřyen, Y.[Yngve], Snizek, B.[Bernhard],
Bicycle Level of Service for Route Choice: A GIS Evaluation of Four Existing Indicators with Empirical Data,
IJGI(8), No. 5, 2019, pp. xx-yy.
DOI Link 1906

Werner, C.[Christian], Resch, B.[Bernd], Loidl, M.[Martin],
Evaluating Urban Bicycle Infrastructures through Intersubjectivity of Stress Sensations Derived from Physiological Measurements,
IJGI(8), No. 6, 2019, pp. xx-yy.
DOI Link 1908

Gu, Z.H.[Zhi-Hui], Zhu, Y.[Yong], Zhang, Y.[Yan], Zhou, W.Y.[Wan-Yu], Chen, Y.[Yu],
Heuristic Bike Optimization Algorithm to Improve Usage Efficiency of the Station-Free Bike Sharing System in Shenzhen, China,
IJGI(8), No. 5, 2019, pp. xx-yy.
DOI Link 1906

Lee, J.S.[Jin-Shyan], Jiang, J.W.[Jun-Wei],
Enhanced fuzzy-logic-based power-assisted control with user-adaptive systems for human-electric bikes,
IET-ITS(13), No. 10, October 2019, pp. 1492-1498.
DOI Link 1909

Sweeney, S., Ordóńez-Hurtado, R., Pilla, F., Russo, G., Timoney, D., Shorten, R.,
A Context-Aware E-Bike System to Reduce Pollution Inhalation While Cycling,
ITS(20), No. 2, February 2019, pp. 704-715.
Sensors, Electric motors, Air pollution, Automobiles, Batteries, Urban areas, Cyber-physics, pollution mitigation, pedelecs, man-machine interaction BibRef

Huang, F., Qiao, S., Peng, J., Guo, B.,
A Bimodal Gaussian Inhomogeneous Poisson Algorithm for Bike Number Prediction in a Bike-Sharing System,
ITS(20), No. 8, August 2019, pp. 2848-2857.
Predictive models, Nonhomogeneous media, Meteorology, Prediction algorithms, Public transportation, Neural networks, time series prediction BibRef

Cheng, X.Q.[Xiao-Qian], Li, C.M.[Cheng-Ming], Du, W.B.[Wei-Bing], Shen, J.M.[Jian-Ming], Dai, Z.X.[Zhao-Xin],
Trip Extraction of Shared Electric Bikes Based on Multi-Rule-Constrained Homomorphic Linear Clustering Algorithm,
IJGI(8), No. 12, 2019, pp. xx-yy.
DOI Link 1912

Zhai, Y.[Yong], Liu, J.[Jin], Du, J.[Juan], Wu, H.[Hao],
Fleet Size and Rebalancing Analysis of Dockless Bike-Sharing Stations Based on Markov Chain,
IJGI(8), No. 8, 2019, pp. xx-yy.
DOI Link 1909

Dong, J.[Jian], Chen, B.[Bin], He, L.[Lingnan], Ai, C.[Chuan], Zhang, F.[Fang], Guo, D.[Danhuai], Qiu, X.G.[Xiao-Gang],
A Spatio-Temporal Flow Model of Urban Dockless Shared Bikes Based on Points of Interest Clustering,
IJGI(8), No. 8, 2019, pp. xx-yy.
DOI Link 1909

Christian, K.[Kapuku], Cho, S.H.[Shin-Hyung], Kho, S.Y.[Seung-Young], Kim, D.K.[Dong-Kyu],
Bayesian models with spatial autocorrelation for bike sharing ridership variability based on revealed preference GPS trajectory data,
IET-ITS(13), No. 11, November 2019, pp. 1658-1667.
DOI Link 1911

Cao, M.[Min], Ma, S.J.[Shang-Jing], Huang, M.X.[Meng-Xue], Lü, G.N.[Guo-Nian], Chen, M.[Min],
Effects of Free-Floating Shared Bicycles on Urban Public Transportation,
IJGI(8), No. 8, 2019, pp. xx-yy.
DOI Link 1909

Zhao, X.F.[Xiao-Fei], Hu, C.Y.[Cai-Yi], Liu, Z.[Zhao], Meng, Y.Y.[Yang-Yang],
Weighted Dynamic Time Warping for Grid-Based Travel-Demand-Pattern Clustering: Case Study of Beijing Bicycle-Sharing System,
IJGI(8), No. 6, 2019, pp. xx-yy.
DOI Link 1908

Cao, M.[Min], Cai, B.Q.[Bo-Qin], Ma, S.J.[Shang-Jing], Lü, G.N.[Guo-Nian], Chen, M.[Min],
Analysis of the Cycling Flow Between Origin and Destination for Dockless Shared Bicycles Based on Singular Value Decomposition,
IJGI(8), No. 12, 2019, pp. xx-yy.
DOI Link 1912

Yang, Z., Chen, J., Hu, J., Shu, Y., Cheng, P.,
Mobility Modeling and Data-Driven Closed-Loop Prediction in Bike-Sharing Systems,
ITS(20), No. 12, December 2019, pp. 4488-4499.
Predictive models, Bicycles, Urban areas, Optimization, Meteorology, Probabilistic logic, Bike-sharing, mobility modeling, Monte Carlo simulation BibRef

Bao, J.[Jie], Yu, H.[Hao], Wu, J.M.[Jia-Ming],
Short-term FFBS demand prediction with multi-source data in a hybrid deep learning framework,
IET-ITS(13), No. 9, September 2019, pp. 1340-1347.
DOI Link 1908
Short-term demand of free-floating bike sharing. BibRef

Wang, S.F.[Shuo-Feng], Li, Z.H.[Zhi-Heng], Gu, R.[Ruochen], Xie, N.[Na],
Placement optimisation for station-free bicycle-sharing under 1D distribution assumption,
IET-ITS(14), No. 9, September 2020, pp. 1079-1086.
DOI Link 2008

Ren, Y., Zhao, F., Jin, H., Jiao, Z., Meng, L., Zhang, C., Sutherland, J.W.,
Rebalancing Bike Sharing Systems for Minimizing Depot Inventory and Traveling Costs,
ITS(21), No. 9, September 2020, pp. 3871-3882.
Bicycles, Routing, Mathematical model, Vehicle dynamics, Mathematical programming, Biological system modeling, mathematical programming BibRef

Chen, P.C.[Po-Chuan], Hsieh, H.Y.[He-Yen], Su, K.W.[Kuan-Wu], Sigalingging, X.K.[Xanno Kharis], Chen, Y.R.[Yan-Ru], Leu, J.S.[Jenq-Shiou],
Predicting station level demand in a bike-sharing system using recurrent neural networks,
IET-ITS(14), No. 6, June 2020, pp. 554-561.
DOI Link 2005

Ye, M.[Mao], Zeng, S.[Simeng], Yang, G.X.[Gui-Xin], Chen, Y.J.[Ya-Jing],
Identification of contributing factors on travel mode choice among different resident types with bike-sharing as an alternative,
IET-ITS(14), No. 7, July 2020, pp. 639-646.
DOI Link 2006

Hua, M.Z.[Ming-Zhuang], Chen, J.X.[Jing-Xu], Chen, X.W.[Xue-Wu], Gan, Z.X.[Zuo-Xian], Wang, P.F.[Peng-Fei], Zhao, D.[De],
Forecasting usage and bike distribution of dockless bike-sharing using journey data,
IET-ITS(14), No. 12, December 2020, pp. 1647-1656.
DOI Link 2011

Jin, X.T.[Xue-Ting], Tong, D.Q.[Dao-Qin],
Station-Free Bike Rebalancing Analysis: Scale, Modeling, and Computational Challenges,
IJGI(9), No. 11, 2020, pp. xx-yy.
DOI Link 2012

Cheng, X.Q.[Xiao-Qian], Du, W.B.[Wei-Bing], Li, C.M.[Cheng-Ming], Yang, L.K.[Lei-Ku], Xu, L.J.[Lin-Juan],
Exploring the Attractiveness of Residential Areas for Human Activities Based on Shared E-Bike Trajectory Data,
IJGI(9), No. 12, 2020, pp. xx-yy.
DOI Link 2012

Sathishkumar, V.E., Park, J.[Jangwoo], Cho, Y.Y.[Yong-Yun],
Seoul bike trip duration prediction using data mining techniques,
IET-ITS(14), No. 11, November 2020, pp. 1465-1474.
DOI Link 2010

Albuquerque, V.[Vitória], Dias, M.S.[Miguel Sales], Bacao, F.[Fernando],
Machine Learning Approaches to Bike-Sharing Systems: A Systematic Literature Review,
IJGI(10), No. 2, 2021, pp. xx-yy.
DOI Link 2103

Gao, F.[Feng], Li, S.Y.[Shao-Ying], Tan, Z.Z.[Zhang-Zhi], Zhang, X.M.[Xiao-Ming], Lai, Z.P.[Zhi-Peng], Tan, Z.[Ziling],
How Is Urban Greenness Spatially Associated with Dockless Bike Sharing Usage on Weekdays, Weekends, and Holidays?,
IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link 2104

Fan, R.N.[Rui-Na], Ma, F.Q.[Fan-Qi],
Bike-sharing systems with a dual selection mechanism and a dynamic double-threshold repositioning policy,
IET-ITS(15), No. 5, 2021, pp. 712-725.
DOI Link 2106

Wang, W.[Wei], Zhao, X.F.[Xiao-Feng], Gong, Z.G.[Zhi-Guo], Chen, Z.K.[Zhi-Kui], Zhang, N.[Ning], Wei, W.[Wei],
An Attention-Based Deep Learning Framework for Trip Destination Prediction of Sharing Bike,
ITS(22), No. 7, July 2021, pp. 4601-4610.
Machine learning, Task analysis, Neural networks, Smart cities, Convolution, Predictive models, Internet of Things, attention model BibRef

Borowska-Stefanska, M.[Marta], Mikusova, M.[Miroslava], Kowalski, M.[Michal], Kurzyk, P.[Paulina], Wisniewski, S.[Szymon],
Changes in Urban Mobility Related to the Public Bike System with Regard to Weather Conditions and Statutory Retail Restrictions,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109

Bahadori, M.S.[Mohammad Sadegh], Gonçalves, A.B.[Alexandre B.], Moura, F.[Filipe],
A Systematic Review of Station Location Techniques for Bicycle-Sharing Systems Planning and Operation,
IJGI(10), No. 8, 2021, pp. xx-yy.
DOI Link 2108

Zhang, X.Y.[Xiao-Yi], Chen, Y.R.[Yu-Rong], Zhong, Y.[Yang],
Spatial and Temporal Characteristic Analysis of Imbalance Usage in the Hangzhou Public Bicycle System,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link 2110

Chen, L.J.[Li-Jun], Zhang, H.P.[Hai-Ping], Wang, H.R.[Hao-Ran], Wu, P.[Peng],
Understanding Plum Rain's Effects on Urban Public Bicycle Unavailability Considering Both Place Semantics and Riding Distance,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link 2110

Lee, J.[Jiwon], Yu, K.[Kiyun], Kim, J.Y.[Ji-Young],
Public Bike Trip Purpose Inference Using Point-of-Interest Data,
IJGI(10), No. 5, 2021, pp. xx-yy.
DOI Link 2106

Jiang, G.Y.[Guan-Ying], Zhang, R.H.[Rong-Hui], Qu, X.B.[Xiao-Bo], Zhao, D.Z.[De-Zong],
A Dynamic Model Averaging for the Discovery of Time-Varying Weather-Cycling Patterns,
ITS(22), No. 5, May 2021, pp. 2786-2796.
Weather impacts cyclists. Scheduling bike trips. Predictive models, Production, Weather forecasting, Urban areas, Wind speed, Intelligent transportation systems. BibRef

Capodici, A.E.[Alessandro Emilio], d'Orso, G.[Gabriele], Migliore, M.[Marco],
A GIS-Based Methodology for Evaluating the Increase in Multimodal Transport between Bicycle and Rail Transport Systems. A Case Study in Palermo,
IJGI(10), No. 5, 2021, pp. xx-yy.
DOI Link 2106

Phithakkitnukooon, S.[Santi], Patanukhom, K.[Karn], Demissie, M.G.[Merkebe Getachew],
Predicting Spatiotemporal Demand of Dockless E-Scooter Sharing Services with a Masked Fully Convolutional Network,
IJGI(10), No. 11, 2021, pp. xx-yy.
DOI Link 2112

Chen, L.J.[Li-Jun], Jiang, S.J.[Shang-Jing],
Spatiotemporal Polyrhythm Characteristics of Public Bicycle Mobility in Urban Chronotopes Context,
IJGI(11), No. 1, 2022, pp. xx-yy.
DOI Link 2201

Lock, O.[Oliver], Pettit, C.[Christopher],
Developing Participatory Analytics Techniques to Inform the Prioritisation of Cycling Infrastructure,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202

Jiang, M.[Mingda], Li, C.[Chao], Li, K.[Kehan], Liu, H.[Hao],
Destination Prediction Based on Virtual POI Docks in Dockless Bike-Sharing System,
ITS(23), No. 3, March 2022, pp. 2457-2470.
Legged locomotion, Probabilistic logic, Roads, Global Positioning System, Feature extraction, Buildings, virtual dock BibRef

Walker, J.[Jeremy], Poliziani, C.[Cristian], Tortora, C.[Cristina], Schweizer, J.[Joerg], Rupi, F.[Federico],
Nonparametric Regression Analysis of Cyclist Waiting Times across Three Behavioral Typologies,
IJGI(11), No. 3, 2022, pp. xx-yy.
DOI Link 2204

Chen, X.[Xian], Jiang, H.[Hai],
Detecting the Demand Changes of Bike Sharing: A Bayesian Hierarchical Approach,
ITS(23), No. 5, May 2022, pp. 3969-3984.
Hidden Markov models, Bayes methods, Linear regression, Numerical models, Indexes, Data models, Timing, Bayesian hierarchical models BibRef

Kondor, D.[Dániel], Zhang, X.[Xiaohu], Meghjani, M.[Malika], Santi, P.[Paolo], Zhao, J.H.[Jin-Hua], Ratti, C.[Carlo],
Estimating the Potential for Shared Autonomous Scooters,
ITS(23), No. 5, May 2022, pp. 4651-4662.
Motorcycles, Transportation, Bicycles, Urban areas, Autonomous vehicles, Uncertainty, Propulsion, Autonomous vehicles, first- and last-mile transportation BibRef

Kim, K.[Kyoungok],
Spatial Contiguity-Constrained Hierarchical Clustering for Traffic Prediction in Bike Sharing Systems,
ITS(23), No. 6, June 2022, pp. 5754-5764.
Clustering algorithms, Prediction algorithms, Predictive models, Heuristic algorithms, Convergence, Clustering methods, random forest BibRef

Li, X.Y.[Xin-Yu], Xu, Y.[Yang], Chen, Q.[Qi], Wang, L.[Lei], Zhang, X.[Xiaohu], Shi, W.Z.[Wen-Zhong],
Short-Term Forecast of Bicycle Usage in Bike Sharing Systems: A Spatial-Temporal Memory Network,
ITS(23), No. 8, August 2022, pp. 10923-10934.
Bicycles, Deep learning, Predictive models, Urban areas, Feature extraction, Convolution, Task analysis, Bike sharing, shared mobility BibRef

Wang, J.[Junheng], Li, F.[Fan], Yang, S.[Song], Li, Y.Q.[You-Qi], Wang, Y.[Yu],
A Real-Time Bike Trip Planning Policy With Self-Organizing Bike Redistribution,
ITS(23), No. 8, August 2022, pp. 10646-10661.
Real-time systems, Planning, Routing, Prediction methods, Optimization, Legged locomotion, Fans, Bike trip planning, queueing BibRef

Xiao, X.[Xiao], Zhang, Y.L.[Yun-Long], Yang, S.[Shu], Kong, X.Q.[Xiao-Qiang],
Efficient Missing Counts Imputation of a Bike-Sharing System by Generative Adversarial Network,
ITS(23), No. 8, August 2022, pp. 13443-13451.
Generative adversarial networks, Transportation, Neural networks, Training, Planning, Traffic control, Memory, Traffic data imputation, generative adversarial network BibRef

Ashqar, H.I.[Huthaifa I.], Elhenawy, M.[Mohammed], Rakha, H.A.[Hesham A.], House, L.[Leanna],
Quality of Service Measure for Bike Sharing Systems,
ITS(23), No. 9, September 2022, pp. 15841-15849.
Quality of service, Pollution measurement, Bicycles, Area measurement, Sociology, Stochastic processes, urban computing BibRef

Hu, L.[Lujin], Wen, Z.[Zheng], Wang, J.[Jian], Hu, J.[Jing],
Spatial Interaction Analysis of Shared Bicycles Mobility Regularity and Determinants: A Case Study of Six Main Districts, Beijing,
IJGI(11), No. 9, 2022, pp. xx-yy.
DOI Link 2209

Chen, X.[Xian], Huang, K.[Kun], Jiang, H.[Hai],
Detecting Changes in the Spatiotemporal Pattern of Bike Sharing: A Change-Point Topic Model,
ITS(23), No. 10, October 2022, pp. 18361-18377.
Spatiotemporal phenomena, Hidden Markov models, Pattern recognition, Transportation, Time series analysis, Tensors, topic models BibRef

Zhang, J.H.[Jian-Hui], Zhang, W.Q.[Wan-Qing], Wang, J.C.[Jia-Cheng], Feng, J.W.[Jian-Wen], Gao, Z.G.[Zhi-Gang], Zheng, S.[Siwen],
Rechargeable Battery Cabinet Deployment for Public Bike System,
ITS(23), No. 11, November 2022, pp. 20309-20322.
Urban areas, Batteries, Feature extraction, Quality of service, Public transportation, Genetic algorithms, Mathematical models, city voronoi diagram BibRef

Zhu, Z.[Zheng], Xu, M.[Meng], Di, Y.[Yining], Yang, H.[Hai],
Fitting Spatial-Temporal Data via a Physics Regularized Multi-Output Grid Gaussian Process: Case Studies of a Bike-Sharing System,
ITS(23), No. 11, November 2022, pp. 21090-21101.
Transportation, Computational modeling, Predictive models, Physics, Data models, Task analysis, Deep learning, bike-sharing BibRef

Chao, S.[Sun], Jian, L.[Lu],
Modelling Bottlenecks of Bike-Sharing Travel Using the Distinction between Endogenous and Exogenous Demand: A Case Study in Beijing,
IJGI(11), No. 11, 2022, pp. xx-yy.
DOI Link 2212

Li, X.Y.[Xiang-Yu], Sinniah, G.K.[Gobi Krishna], Li, R.[Ruiwei], Li, X.Q.[Xiao-Qing],
Correlation between Land Use Pattern and Urban Rail Ridership Based on Bicycle-Sharing Trajectory,
IJGI(11), No. 12, 2022, pp. xx-yy.
DOI Link 2301

Xin, R.[Rui], Ding, L.F.[Lin-Fang], Ai, B.[Bo], Yang, M.[Min], Zhu, R.[Ruoxin], Cao, B.[Bin], Meng, L.Q.[Li-Qiu],
Geospatial Network Analysis and Origin-Destination Clustering of Bike-Sharing Activities during the COVID-19 Pandemic,
IJGI(12), No. 1, 2023, pp. xx-yy.
DOI Link 2301

Monteiro, J.[Joăo], Sousa, N.[Nuno], Natividade-Jesus, E.[Eduardo], Coutinho-Rodrigues, J.[Joăo],
The Potential Impact of Cycling on Urban Transport Energy and Modal Share: A GIS-Based Methodology,
IJGI(12), No. 2, 2023, pp. xx-yy.
DOI Link 2303

Lee, S.H.[Shih-Hsiung], Ku, H.C.[Hsuan-Chih],
A Dual Attention-Based Recurrent Neural Network for Short-Term Bike Sharing Usage Demand Prediction,
ITS(24), No. 4, April 2023, pp. 4621-4630.
Bicycles, Trajectory, Predictive models, Feature extraction, Correlation, Time series analysis, Market research, short-term bike sharing usage demand prediction BibRef

Wu, H.[Hao], Wang, Y.H.[Yan-Hui], Sun, Y.Q.[Yu-Qing], Yin, D.D.[Duo-Duo], Li, Z.X.[Zhan-Xing], Luo, X.Y.[Xiao-Yue],
Identification and Spatiotemporal Analysis of Bikesharing-Metro Integration Cycling,
IJGI(12), No. 4, 2023, pp. 166.
DOI Link 2305

Li, L.Q.[Ling-Qiao], Wang, X.[Xiangkai], Yang, M.Y.[Meng-Yu], Zhang, H.W.[Hong-Wei],
An accurate shared bicycle detection network based on faster R-CNN,
IET-IPR(17), No. 6, 2023, pp. 1919-1930.
DOI Link 2305
deformable convolution, feature fusion, object detection application, shared bicycle management BibRef

Wei, Z.H.[Zhong-Hua], Wang, M.Q.[Ming-Qian], Wang, S.[Shaofan],
A worker-and-system trade-off model for rebalancing free-float bike sharing systems: A mixed rebalancing strategy,
IET-ITS(17), No. 5, 2023, pp. 1037-1050.
DOI Link 2305
augmented Lagrange method, bike sharing system, Bureau of Public Roads function, rebalancing problem BibRef

Chai, J.[Jun], Song, J.[Jun], Fan, H.W.[Hong-Wei], Xu, Y.[Yibo], Zhang, L.[Le], Guo, B.[Bing], Xu, Y.W.[Ya-Wen],
ST-Bikes: Predicting Travel-Behaviors of Sharing-Bikes Exploiting Urban Big Data,
ITS(24), No. 7, July 2023, pp. 7676-7686.
Predictive models, Data models, Roads, Urban areas, Time series analysis, Meteorology, Public transportation, travel-behaviors 4G/5G/6G communication BibRef

Wei, B.[Baohua], Zhu, L.[Lei],
Exploring the Impact of Built Environment Factors on the Relationships between Bike Sharing and Public Transportation: A Case Study of New York,
IJGI(12), No. 7, 2023, pp. xx-yy.
DOI Link 2308

Xu, Y.M.[Yi-Ming], Zhao, X.[Xilei], Zhang, X.J.[Xiao-Jian], Paliwal, M.[Mudit],
Real-Time Forecasting of Dockless Scooter-Sharing Demand: A Spatio-Temporal Multi-Graph Transformer Approach,
ITS(24), No. 8, August 2023, pp. 8507-8518.
Predictive models, Meteorology, Transportation, Transformers, Spatiotemporal phenomena, Real-time systems, Motorcycles, shared micromobility BibRef

Shi, Y.[Yan], Wang, D.[Da], Wang, X.L.[Xiao-Long], Chen, B.[Bingrong], Ding, C.[Chen], Gao, S.[Shijuan],
Sensing Travel Source-Sink Spatiotemporal Ranges Using Dockless Bicycle Trajectory via Density-Based Adaptive Clustering,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link 2308

Suárez-Vega, R.[Rafael], Santana-Jiménez, Y.[Yolanda], Hernández, J.M.[Juan M.], Santana-Figueroa, J.J.[José Juan],
Assessment of the Bike-Sharing Socioeconomic Equity in the Use of Routes,
IJGI(12), No. 8, 2023, pp. 320.
DOI Link 2309

Wang, J.B.[Jian-Biao], Miwa, T.[Tomio], Morikawa, T.[Takayuki],
A Demand Truncation and Migration Poisson Model for Real Demand Inference in Free-Floating Bike-Sharing System,
ITS(24), No. 10, October 2023, pp. 10525-10536.

Ebnealipour, S.[Sohrab], Masih-Tehrani, M.[Masoud], Nazemian, H.[Hossein],
A novel e-bike energy management for improvement of the rider metabolism,
IET-ITS(17), No. 10, 2023, pp. 1964-1978.
DOI Link 2310
automotive electrics, bicycles, electric vehicles, energy management systems, optimisation BibRef

Chen, D.W.[Da-Wei], Chen, Q.[Qun], Imdahl, C.[Christina], van Woensel, T.[Tom],
A Rolling-Horizon Strategy for Dynamic Rebalancing of Free-Floating Bike-Sharing Systems,
ITS(24), No. 11, November 2023, pp. 12123-12140.

Toro, J.F., Carrion, D., Brovelli, M.A., Percoco, M.,
Bikemi Bike-sharing Service Exploratory Analysis on Mobility Patterns,
DOI Link 2012

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Transit Traffic Analysis, Public Transit, Bus .

Last update:Apr 18, 2024 at 11:38:49