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Optimizing Urban Infrastructure for E-Scooter Mobility

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Applications of Evolutionary Computation (EvoApplications 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14634))

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Abstract

This paper addresses the optimization of urban infrastructure for e-scooter mobility through a multi-criteria approach. The proposed problem considers redesigning road infrastructure to integrate e-scooters into a city’s multimodal transportation system. The objectives involve improving cycle lane coverage for e-scooters while minimizing installation costs. A parallel multi-objective evolutionary algorithm is introduced to solve this problem, applied to a real-world instance based on Málaga city data. The results showcase the algorithm’s effectiveness in exploring the Pareto front, offering diverse trade-off solutions. Key solutions are analyzed, highlighting different zones with varying trade-offs between travel time improvement and installation costs. Visualization of proposed infrastructure changes illustrates significant reductions in travel time and enhanced multimodality. Computational efficiency analysis indicates successful parallelization, achieving substantial speedup and high efficiency with up to 32 processing elements.

This research is partially funded by the Universidad de Málaga (UMA); under grant PID 2020-116727RB-I00 (HUmove) funded by MCIN/AEI/10.13039/501100011033; under grant number PRE2021-100645 by MCIN/AEI/10.13039/501100011033 and by the FSE+; and TAILOR ICT-48 Network (No 952215) funded by EU Horizon 2020 research and innovation programme.The authors thank the Supercomputing and Bioinformatics center at the UMA for their computer resources and assistance.

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Notes

  1. 1.

    Málaga Subway website: www.metromalaga.es.

  2. 2.

    Github of the project: https://github.com/pedrozad/e-scooter-way.

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Authors and Affiliations

  1. ITIS Software, Universidad de Málaga, Málaga, Spain

    Diego Daniel Pedroza-Perez, Jamal Toutouh & Gabriel Luque

Authors
  1. Diego Daniel Pedroza-Perez
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  2. Jamal Toutouh
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  3. Gabriel Luque
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Corresponding author

Correspondence to Diego Daniel Pedroza-Perez .

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Editors and Affiliations

  1. University of York, York, UK

    Stephen Smith

  2. University of Coimbra, Coimbra, Portugal

    João Correia

  3. University of Málaga, Málaga, Spain

    Christian Cintrano

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Pedroza-Perez, D.D., Toutouh, J., Luque, G. (2024). Optimizing Urban Infrastructure for E-Scooter Mobility. In: Smith, S., Correia, J., Cintrano, C. (eds) Applications of Evolutionary Computation. EvoApplications 2024. Lecture Notes in Computer Science, vol 14634. Springer, Cham. https://doi.org/10.1007/978-3-031-56852-7_22

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  • DOI: https://doi.org/10.1007/978-3-031-56852-7_22

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