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A Study of an Ant-Based Algorithm to Model Cyclist Behavior in Bicycle-Friendly Cities

  • 2026
  • OriginalPaper
  • Chapter
Published in:
Authors
Felix Repusseau
Emmanuel Néron
Tifenn Rault
Nicolas Monmarché
Published in
Artificial Evolution
Publisher
Springer Nature Switzerland

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Abstract

This study delves into the application of an ant-based algorithm to model cyclist behavior in bicycle-friendly cities, focusing on the critical factors of distance and danger. The research introduces an ant colony optimization (ACO) algorithm tailored to simulate cyclists' path choices, aiming to enhance cycling networks. Key topics include the development of the ACO algorithm, parameter settings, and experimental results that demonstrate the algorithm's ability to improve upon existing cycling routes. The study also explores the influence of data order and pheromone values, providing a comprehensive analysis of the algorithm's performance. The findings suggest that the ant algorithm can effectively model cyclist behavior, offering a promising tool for urban planners and transportation experts to optimize cycling infrastructure.
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previous chapter Optimizing Scheduling for Energy Sales in Public Stations: A Revenue Management Perspective
next chapter Paving the Way Towards Evolutionary Machine Teaching: An Application to 4-Part Harmony
Title
A Study of an Ant-Based Algorithm to Model Cyclist Behavior in Bicycle-Friendly Cities
Authors
Felix Repusseau
Emmanuel Néron
Tifenn Rault
Nicolas Monmarché
Copyright Year
2026
Book
Artificial Evolution

Print ISBN: 978-3-032-07997-8

Electronic ISBN: 978-3-032-07998-5

Copyright Year: 2026

DOI
https://doi.org/10.1007/978-3-032-07998-5_4
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