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Scheduling System for Multiple Self-driving Cars Using K-Means and Bio-inspired Optimization Algorithms

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Abstract

This paper presents the development of a hybrid approach as a solution to the multiple Traveling Salesman Problem (mTSP) applied to the route scheduling for self-drive cars. First, we use k-means to generate routes that equality distribute delivery locations among the cars. Then, these routes are set as the initial population for bio-inspired algorithms, such as Genetic Algorithm (GA) and Ant Colony System (ACS), which perform an evolutionary process to find a route which minimizes the overall distance while keeping the balance of individual tours of each car. The experiments were conducted with our route scheduling system in real and virtual environments. We compared our hybrid approaches using k-means in conjunction with GA and ACS against GA, ACS, and Particle Swarm Optimization (PSO) initialized with random population. The results showed that, as the number of cars and target locations increase, the hybrid modeling approaches outperform GA, ACS, and PSO without any pre-processing.

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Data availability

The data that support this study cannot be made available due to the fact that the test scenarios were generated in our centralized system. However, we can provide the developed system. If it is of interest to the reader of this article, he may contact the corresponding author.

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Funding

This study was funded by Federal University of Uberlândia, and by the CNPq (Grant No. 400699/2016-8).

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Authors and Affiliations

  1. Faculty of Computing, Federal University of Uberlândia, Uberlândia, Minas Gerais, Brazil

    Clênio E. Silva, Raulcézar Alves & Jefferson R. Souza

  2. Institute of Mathematical and Computer Sciences, University of São Paulo, São Carlos, São Paulo, Brazil

    Tiago S. César, Iago P. Gomes, Júnior A. R. Silva & Denis F. Wolf

Authors
  1. Clênio E. Silva
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  2. Tiago S. César
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  3. Iago P. Gomes
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  4. Júnior A. R. Silva
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  5. Denis F. Wolf
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  6. Raulcézar Alves
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  7. Jefferson R. Souza
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Corresponding authors

Correspondence to Clênio E. Silva, Raulcézar Alves or Jefferson R. Souza.

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This article is part of the topical collection “Machine Learning Modeling Techniques and Applications” guest edited by Lazaros Iliadis, Elias Pimenidis and Chrisina Jayne.

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Silva, C.E., César, T.S., Gomes, I.P. et al. Scheduling System for Multiple Self-driving Cars Using K-Means and Bio-inspired Optimization Algorithms. SN COMPUT. SCI. 4, 647 (2023). https://doi.org/10.1007/s42979-023-02053-z

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