Taxonomia das Abordagens Computacionais para Apoio à Decisão no Transporte Público Urbano: Uma Revisão Comparativa da Literatura
Resumo
Este trabalho propõe uma taxonomia das abordagens computacionais aplicadas ao apoio à decisão no transporte público urbano, construída por meio de uma revisão comparativa da literatura. Estudos representativos foram analisados segundo o problema abordado, a abordagem computacional empregada e o nível de apoio à decisão, permitindo sua organização em quatro categorias: estratégica, tática, operacional e informação em tempo real. A taxonomia organiza pesquisas tradicionalmente classificadas por tecnologia sob uma perspectiva orientada ao processo decisório, evidenciando complementaridades entre diferentes abordagens computacionais e identificando oportunidades de pesquisa, especialmente no nível tático. Como principal contribuição, o trabalho apresenta um referencial conceitual para apoiar a organização e a análise de pesquisas em Computação aplicada ao transporte público urbano.Referências
Ali, R., Hussain, A., Nazir, S., Khan, S., and Khan, H. U. (2023). Intelligent decision support systems—an analysis of machine learning and multicriteria decision-making methods. Applied Sciences, 13(22):12426.
Anthony, R. N. (1965). Planning and Control Systems: A Framework for Analysis. Harvard University Graduate School of Business Administration, Boston, MA.
Basu, A., Raja, B., Gracious, R., and Vanajakshi, L. (2020). Dynamic trip planner for public transport using genetic algorithm. Transport, 35(2):156–167.
de Moraes Ayres Moura, D. (2022). Otimização do transporte público visando a integração entre zonas central e sul de porto alegre utilizando o software de simulação sumo.
Dumitrescu, C., Tăbı̂rcă, A.-I., Stanciu, A., Nemtoi, L., Radu, V., and Gore, B. E. (2025). Ai-based decision support system for attenuating traffic congestion in smart cities. Applied Sciences, 15(21):11470.
Elassy, M., Al-Hattab, M., Takruri, M., and Badawi, S. (2024). Intelligent transportation systems for sustainable smart cities. Transportation Engineering, 16:100252.
Hassan, M. A., Javed, R., Farhatullah, Granelli, F., Gen, X., Rizwan, M., Ali, S. H., Junaid, H., and Ullah, S. (2023). Intelligent transportation systems in smart city: A systematic survey. In 2023 International Conference on Robotics and Automation in Industry (ICRAI), pages 1–9.
Iliopoulou, C. and Kepaptsoglou, K. (2019). Combining its and optimization in public transportation planning: State of the art and future research paths. European Transport Research Review, 11(1):27.
Jain, Y. and Pandey, K. (2025). Transforming urban mobility: A systematic review of ai-based traffic optimization techniques. Archives of Computational Methods in Engineering, 32:5381–5417.
Li, C., Ge, R., Wu, X., and Khamis, A. (2023). Optimal placement of bus stops using particle swarm optimization. In 2023 IEEE International Conference on Smart Mobility (SM), pages 15–20.
Mavlutova, I., Atstaja, D., Grasis, J., Kuzmina, J., Uvarova, I., and Roga, D. (2023). Urban transportation concept and sustainable urban mobility in smart cities: A review. Energies, 16(8):3585.
Miguel, I., Mendonça, J., Olivé, J., and Andrade, A. R. (2025). Assessing time savings as bus rapid transit is introduced in barcelona: A bus network design approach. Public Transport, 17:611–634.
Nickerson, R. C., Varshney, U., and Muntermann, J. (2013). A method for taxonomy development and its application in information systems. In Proceedings of the European Conference on Information Systems (ECIS), Utrecht, The Netherlands.
Owais, M., Moussa, G., Abbas, Y., and El-Shabrawy, M. (2014). Simple and effective solution methodology for transit network design problem. International Journal of Computer Applications, 89(14):32–40.
Pais, F. V. (2022). Avaliação de desempenho de tráfego urbano usando simulação: Estudo de caso em maceió/al. Master’s thesis, Universidade Federal de Alagoas, Maceió, AL.
Qiao, F., Liu, T., Sun, H., Guo, L., and Chen, Y. (2021). Modelling and simulation of urban traffic systems: present and future. International Journal of Cybernetics and Cyber-Physical Systems, 1(1):1–32.
Rui, J. and Othengrafen, F. (2023). Examining the role of innovative streets in enhancing urban mobility and livability for sustainable urban transition: A review. Sustainability, 15(7):5709.
Simon, H. A. (1977). The New Science of Management Decision. Prentice-Hall, Englewood Cliffs, NJ, revised edition edition.
Wang, F., Ye, M., Zhu, H., and Gu, D. (2022). Optimization method for conventional bus stop placement and the bus line network based on the voronoi diagram. Sustainability, 14(13):7918.
Anthony, R. N. (1965). Planning and Control Systems: A Framework for Analysis. Harvard University Graduate School of Business Administration, Boston, MA.
Basu, A., Raja, B., Gracious, R., and Vanajakshi, L. (2020). Dynamic trip planner for public transport using genetic algorithm. Transport, 35(2):156–167.
de Moraes Ayres Moura, D. (2022). Otimização do transporte público visando a integração entre zonas central e sul de porto alegre utilizando o software de simulação sumo.
Dumitrescu, C., Tăbı̂rcă, A.-I., Stanciu, A., Nemtoi, L., Radu, V., and Gore, B. E. (2025). Ai-based decision support system for attenuating traffic congestion in smart cities. Applied Sciences, 15(21):11470.
Elassy, M., Al-Hattab, M., Takruri, M., and Badawi, S. (2024). Intelligent transportation systems for sustainable smart cities. Transportation Engineering, 16:100252.
Hassan, M. A., Javed, R., Farhatullah, Granelli, F., Gen, X., Rizwan, M., Ali, S. H., Junaid, H., and Ullah, S. (2023). Intelligent transportation systems in smart city: A systematic survey. In 2023 International Conference on Robotics and Automation in Industry (ICRAI), pages 1–9.
Iliopoulou, C. and Kepaptsoglou, K. (2019). Combining its and optimization in public transportation planning: State of the art and future research paths. European Transport Research Review, 11(1):27.
Jain, Y. and Pandey, K. (2025). Transforming urban mobility: A systematic review of ai-based traffic optimization techniques. Archives of Computational Methods in Engineering, 32:5381–5417.
Li, C., Ge, R., Wu, X., and Khamis, A. (2023). Optimal placement of bus stops using particle swarm optimization. In 2023 IEEE International Conference on Smart Mobility (SM), pages 15–20.
Mavlutova, I., Atstaja, D., Grasis, J., Kuzmina, J., Uvarova, I., and Roga, D. (2023). Urban transportation concept and sustainable urban mobility in smart cities: A review. Energies, 16(8):3585.
Miguel, I., Mendonça, J., Olivé, J., and Andrade, A. R. (2025). Assessing time savings as bus rapid transit is introduced in barcelona: A bus network design approach. Public Transport, 17:611–634.
Nickerson, R. C., Varshney, U., and Muntermann, J. (2013). A method for taxonomy development and its application in information systems. In Proceedings of the European Conference on Information Systems (ECIS), Utrecht, The Netherlands.
Owais, M., Moussa, G., Abbas, Y., and El-Shabrawy, M. (2014). Simple and effective solution methodology for transit network design problem. International Journal of Computer Applications, 89(14):32–40.
Pais, F. V. (2022). Avaliação de desempenho de tráfego urbano usando simulação: Estudo de caso em maceió/al. Master’s thesis, Universidade Federal de Alagoas, Maceió, AL.
Qiao, F., Liu, T., Sun, H., Guo, L., and Chen, Y. (2021). Modelling and simulation of urban traffic systems: present and future. International Journal of Cybernetics and Cyber-Physical Systems, 1(1):1–32.
Rui, J. and Othengrafen, F. (2023). Examining the role of innovative streets in enhancing urban mobility and livability for sustainable urban transition: A review. Sustainability, 15(7):5709.
Simon, H. A. (1977). The New Science of Management Decision. Prentice-Hall, Englewood Cliffs, NJ, revised edition edition.
Wang, F., Ye, M., Zhu, H., and Gu, D. (2022). Optimization method for conventional bus stop placement and the bus line network based on the voronoi diagram. Sustainability, 14(13):7918.
Publicado
23/09/2026
Como Citar
COSTA, Anna Clara da Silva; FERRO, Marcio Roberio da Costa; TIBURCIO, Pablo Gustavo Soares; LIMA, David Henrique de Souza.
Taxonomia das Abordagens Computacionais para Apoio à Decisão no Transporte Público Urbano: Uma Revisão Comparativa da Literatura. In: ESCOLA REGIONAL DE COMPUTAÇÃO BAHIA, ALAGOAS E SERGIPE (ERBASE), 26. , 2026, Maragogi/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 269-278.
DOI: https://doi.org/10.5753/erbase.2026.32313.
