2-Level Station Location for Bike Sharing

2020 ◽  
pp. 108-118
Author(s):  
Fengmin Wang ◽  
Xiaodong Hu ◽  
Chenchen Wu
Keyword(s):  
Bike Sharing ◽  
Station Location

scholarly journals Structure and dynamics of a public bike-sharing system. Case study of the public transport system in Białystok

2016 ◽  
Vol 8 (4) ◽  
pp. 59-66 ◽  
Author(s):  
Ewa Dobrzyńska ◽  
Maciej Dobrzyński
Keyword(s):  
Network Nodes ◽  
The Public ◽  
Public Transport System ◽  
Process Support ◽  
Bike Sharing ◽  
Prognostic Utility ◽  
Decision Making Processes ◽  
Network Metrics ◽  
Station Location ◽  
The Impact

Abstract The article presents the results of a research project referring to the dynamics of the public bike-sharing system BiKeR (Białystok, Poland) in 2014-2015. Identification of the dynamics of the system permits modifications that lead to the enhancement of the efficiency and help to determine the reasons for the choice of a location for new bicycle stations. The basic methodology used for compiling data were the statistical methods with special emphasis on network analysis and graph theory. Analysis of the data allowed us to identify the mechanisms of changes in the system affecting its dynamics, especially in the area of network topology changes in conjunction with the location of network nodes (stations). The research and analysis showed the specificity of PBS as a transport network. The PBS network, the process of analysis, the value of network metrics and their distribution differ significantly from other types of transport networks (including municipal). The results improve decision-making processes related to the creation and modification of a PBS network, especially in the field of process support, the choice of station location and the impact of these choices on the networks dynamics (as a prognostic utility).

scholarly journals Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network

2021 ◽  
Vol 12 (2) ◽  
pp. 1-22
Author(s):  
Jianguo Chen ◽  
Kenli Li ◽  
Keqin Li ◽  
Philip S. Yu ◽  
Zeng Zeng
Keyword(s):  
Large Scale ◽  
Sequence Data ◽  
Location Prediction ◽  
City Management ◽  
Dynamic Planning ◽  
Graph Sequence ◽  
Graph Modeling ◽  
The Government ◽  
Location Clustering ◽  
Station Location

Benefiting from convenient cycling and flexible parking locations, the Dockless Public Bicycle-sharing (DL-PBS) network becomes increasingly popular in many countries. However, redundant and low-utility stations waste public urban space and maintenance costs of DL-PBS vendors. In this article, we propose a Bicycle Station Dynamic Planning (BSDP) system to dynamically provide the optimal bicycle station layout for the DL-PBS network. The BSDP system contains four modules: bicycle drop-off location clustering, bicycle-station graph modeling, bicycle-station location prediction, and bicycle-station layout recommendation. In the bicycle drop-off location clustering module, candidate bicycle stations are clustered from each spatio-temporal subset of the large-scale cycling trajectory records. In the bicycle-station graph modeling module, a weighted digraph model is built based on the clustering results and inferior stations with low station revenue and utility are filtered. Then, graph models across time periods are combined to create a graph sequence model. In the bicycle-station location prediction module, the GGNN model is used to train the graph sequence data and dynamically predict bicycle stations in the next period. In the bicycle-station layout recommendation module, the predicted bicycle stations are fine-tuned according to the government urban management plan, which ensures that the recommended station layout is conducive to city management, vendor revenue, and user convenience. Experiments on actual DL-PBS networks verify the effectiveness, accuracy, and feasibility of the proposed BSDP system.

scholarly journals Abstracting mobility flows from bike-sharing systems

2021 ◽  
Author(s):  
Fabio Kon ◽  
Éderson Cássio Ferreira ◽  
Higor Amario de Souza ◽  
Fábio Duarte ◽  
Paolo Santi ◽  
...  
Keyword(s):  
Bike Sharing
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