Bike Usage Forecasting for Optimal Rebalancing Operations in Bike-Sharing Systems

Simon Ruffieux · Elena Mugellini · Omar Abou Khaled

24 citations0/0 files storedIEEE International Conference on Tools with Artificial Intelligence (ICTAI)

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Urban Transport and Accessibility Transportation and Mobility Innovations Traffic Prediction and Management Techniques

Abstract

This article presents the first step of a project focusing on enhancing the management of bike-sharing systems. The objective of the project is to optimize the daily rebalancing operations that need to be performed by operators of bike-sharing systems using machine-learning algorithms and constraint programming. This study presents an evaluation of machine learning algorithms developed for forecasting the availability of bikes on three Swiss bike-sharing networks. The results demonstrate the superiority of the Multi-Layer Perceptron algorithm for forecasting available bikes at station-level for different prediction horizons and its applicability for real-time prediction generation.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 24 citations exist upstream.

References

2016Rebalancing Bike Sharing Systems 2016Mobility Modeling and Prediction in Bike-Sharing Systems 2018A Dynamic Approach to Rebalancing Bike-Sharing Systems 2015Bike sharing station placement leveraging heterogeneous urban open data 2012Cityride: A Predictive Bike Sharing Journey Advisor 2014Predicting bikeshare system usage up to one day ahead 2016Bike-sharing systems: User dissatisfaction in the presence of unusable bicycles 2016Perceptually important points of mobility patterns to characterise bike sharing systems: The Dublin case

Cited by

2019A Multi-Categorical Probabilistic Approach for Short-Term Bike Sharing Usage Prediction 2020Decision-making on development of cycling infrastructure through safety assessment at design and operation stages 2022Mobility prediction for uneven distribution of bikes in bike sharing systems 2024Prediction of bike-sharing station demand using explainable artificial intelligence 2021A Real-Time Bike Trip Planning Policy With Self-Organizing Bike Redistribution

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.