Pareamento Ponto-a-Rota para Otimização da Última Milha em Sistemas Institucionais de Compartilhamento Veicular
Resumo
Sistemas de carona enfrentam um dilema entre eficiência e qualidade do pareamento. Abordagens Ponto-a-Ponto (P2P) ignoram embarques ao longo da rota, gerando desvios excessivos. Este trabalho apresenta o Caronnect, um sistema Ponto-a-Rota (P2R) para o nicho institucional. O algoritmo analisa a trajetória arterial do motorista para identificar pontos de encontro ideais. A avaliação experimental com 10.000 requisições demonstrou que o Caronnect elevou a taxa de sucesso em 7,7% e reduziu a caminhada do passageiro em 12% frente ao P2P, superando as limitações geométricas de modelos baseados apenas na origem. Quanto à escalabilidade, o sistema manteve comportamento linear e resposta em tempo real (51,89ms para 1.000 motoristas).
Referências
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Souza, A. M., Yokoyama, R. S., Maia, G., Loureiro, A. A. F., and Villas, L. A. (2016). Real-time path planning to prevent traffic jam through an intelligent transportation system. In Proceedings of the 2016 IEEE Symposium on Computers and Communication (ISCC), pages 1–6. IEEE.
Tosoni, F., Ferragina, P., Marino, A., Resta, G., and Santi, P. (2022). Locality filtering for efficient ride sharing platforms. IEEE Transactions on Intelligent Transportation Systems, 23(7):7785–7804.
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Badr, M. M., Baza, M., Abdelfattah, S., Mahmoud, M., and Alasmary, W. (2021). Blockchain-based ride-sharing system with accurate matching and privacy-preservation. In 2021 International Symposium on Networks, Computers and Communications (ISNCC), pages 1–8.
Baudru, J. and Bersini, H. (2024). The comparative analysis of car-pooling algorithms for ride-sharing systems. In Proceedings of the FARI AI Institute Workshop. FARI - AI Institute for the Common Good, Brussels.
Brito, M., Santos, C., Martins, B. S., and Rosário, D. (2024). Context-aware multi-modal route selection service for urban computing scenarios. Ad Hoc Networks, 156:103407.
Bunjkar, S. P. et al. (2015). A carpool system using genetic algorithm. International Journal of Computer Science and Technology, 6(2):53–56.
Bynd (2024). Bynd caronas - Mobilidade Corporativa. [link]. Acesso em: jan. 2025.
Daniels, R. and Mulley, C. (2013). Explaining walking distance to public transport: The dominance of public transport supply. Journal of Transport and Land Use, 6(2):5–20.
Das, A. et al. (2020). A hybrid multi-objective carpool route optimization technique using genetic algorithm and A* algorithm. Journal of King Saud University - Computer and Information Sciences, 34(10):1–12.
Haghpanah, M. A. et al. (2020). A heuristic nearest neighbor algorithm for peer-to-peer ridesharing. arXiv preprint arXiv:2012.05046.
IBGE (2024). Frota de veículos - Brasil. [link]. Acesso em: jan. 2025.
Liao, Y. et al. (2019). A multi-objective ACO to solve the daily carpool problem. International Journal of Information Technology and Web Engineering (IJITWE), 14(1):1–22.
Ma, S., Zheng, Y., and Wolfson, O. (2013). T-share: A large-scale dynamic taxi ridesharing service. In Proceedings of the 2013 IEEE 29th International Conference on Data Engineering (ICDE), pages 410–421. IEEE.
Mapbox (2026). Mapbox Navigation SDK and Directions API Documentation. [link]. Acesso em: abr. 2026.
Mattos, E. P. d., Domingues, A. C. S. A., Silva, F. A., and Loureiro, A. A. F. (2024). Protect your data and I’ll rank its utility: A framework for utility analysis of anonymized mobility data for smart city applications. Ad Hoc Networks, 162:103554.
Rocha, I. A. et al. (2014). Caronaê UFRJ - Unificando e ampliando as caronas na Cidade Universitária/UFRJ. In Anais do X Encontro Nacional de Engenharia e Desenvolvimento Social (ENEDS).
Sinnott, R. W. (1984). Virtues of the haversine. Sky and Telescope, 68(2):158.
Song, C., Qu, Z., Blumm, N., and Barabási, A.-L. (2010). Limits of predictability in human mobility. Science, 327(5968):1018–1021.
Souza, A. M., Yokoyama, R. S., Maia, G., Loureiro, A. A. F., and Villas, L. A. (2016). Real-time path planning to prevent traffic jam through an intelligent transportation system. In Proceedings of the 2016 IEEE Symposium on Computers and Communication (ISCC), pages 1–6. IEEE.
Tosoni, F., Ferragina, P., Marino, A., Resta, G., and Santi, P. (2022). Locality filtering for efficient ride sharing platforms. IEEE Transactions on Intelligent Transportation Systems, 23(7):7785–7804.
UniCaronas (2007). UniCaronas - Sistema de Caronas Universitárias. [link]. Acesso em: jan. 2025.
Villas, L. A., Boukerche, A., Guidoni, D. L., De Oliveira, H. A. B. F., De Araujo, R. B., and Loureiro, A. A. F. (2014). A spatial correlation aware algorithm to perform efficient data collection in wireless sensor networks. Ad Hoc Networks, 12:69–85.
Zheng, Y., Capra, L., Wolfson, O., and Yang, H. (2014). Urban computing: concepts, methodologies, and applications. ACM Transactions on Intelligent Systems and Technology (TIST), 5(3):1–55.
Publicado
25/05/2026
Como Citar
KAMO, Fabiana Tieko; GAIA, Rebeca Larissa Silva; TYMBURIBÁ, Mateus.
Pareamento Ponto-a-Rota para Otimização da Última Milha em Sistemas Institucionais de Compartilhamento Veicular. In: WORKSHOP DE COMPUTAÇÃO URBANA (COURB), 10. , 2026, Praia do Forte/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 211-224.
ISSN 2595-2706.
DOI: https://doi.org/10.5753/courb.2026.22929.
