Personalized Experience-aware Multi-criteria Route Selection for Smart Mobility
Resumo
Smart urban mobility emerged from the urban citizen’s need for a fast urbanization environment, using personal devices and city infrastructure integration, data generation, and mobility services provided on congested and possibly dangerous urban roads. However, traditional routing services need to consider users’ experience, comfort and health because they usually choose only routes with the shortest paths or less traffic. This work proposes a route selection method based on a personalized preference for different user profiles, and essential geolocated factors from data collection, including crime occurrences and air quality factors. The suggestion method allows safer, healthier, and more pleasant paths for drivers and analytic data for city planners compared to single-criteria route selection approaches.Referências
Bellini, P., Nesi, P., and Pantaleo, G. (2022). Iot-enabled smart cities: A review of concepts, frameworks and key technologies. Applied Sciences, 12(3).
Bibri, S. E. and Krogstie, J. (2020). The emerging data-driven smart city and its innovative applied solutions for sustainability: The cases of london and barcelona. Energy Informatics, 3:1-42.
Brito, M., Santos, C., Oliveira, H., Cerqueira, E., and Rosário, D. (2022). Air pollution calculation for location based social networks multimodal routing service. In VI Workshop de Computação Urbana, pages 280-293. SBC.
Han, X., Hu, X., Wu, H., Shen, B., and Wu, J. (2020). Risk prediction of theft crimes in urban communities: An integrated model of lstm and st-gcn. IEEE Access, 8:217222-217230.
HERE (2023). Build apps with here maps api and sdk platform access: Here developer.
Hsieh, H.-P. and Lin, F. (2022). Recommending taxi routes with an advance reservation - a multi-criteria route planner. International Journal of Urban Sciences, 26(1):162-183.
Kaivonen, S. and Ngai, E. C.-H. (2020). Real-time air pollution monitoring with sensors on city bus. Digital Communications and Networks, 6(1):23-30.
Kelly, F. J. and Kelly, J. (2009). London air quality: a real world experiment in progress. Biomarkers, 14(sup1):5-11. PMID: 19604051.
Legaspi, J., Bhada, S. V., Mathisen, P., and DeWinter, J. (2020). Smart city transportation: A multidisciplinary literature review. In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 957-964.
Liu, D., Tang, J., and Zhang, C. (2019). Application of data analysis in trend prediction of different crime types in london. In Mao, R., Wang, H., Xie, X., and Lu, Z., editors, Data Science, pages 445-467, Singapore. Springer Singapore.
Nguyen, D. C., Ding, M., Pathirana, P. N., Seneviratne, A., Li, J., Niyato, D., Dobre, O., and Poor, H. V. (2022). 6g internet of things: A comprehensive survey. IEEE Internet of Things Journal, 9(1):359-383.
OpenStreetMap, c. (2017). Planet dump retrieved from https://www.openstreetmap.org.
Rodrigues, L. S., Sammarco, M., Detyniecki, M., and Campista, M. E. M. (2021). CRAWDAD dataset ufrj/london-trajectories (v. 2021-03-22). Downloaded from https://crawdad.org/ufrj/london-trajectories/2021-03-22.
Saaty, T. L. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1):9-26. Desicion making by the analytic hierarchy process: Theory and applications.
Sarraf, R. and McGuire, M. P. (2020). Integration and comparison of multi-criteria decision making methods in safe route planner. Expert Systems with Applications, 154:113399.
Savithramma, R. M., Ashwini, B. P., and Sumathi, R. (2022). Smart mobility implementation in smart cities: A comprehensive review on state-of-art technologies. In 2022 4th International Conference on Smart Systems and Inventive Technology (ICSSIT), pages 10-17.
Solé, L., Sammarco, M., Detyniecki, M., and M. Campista, M. E. (2022). Towards drivers' safety with multi-criteria car navigation systems. Future Gener. Comput. Syst., 135(C):1-9.
Wu, M.-Y., Ke, C.-K., and Lai, S.-C. (2022). Optimizing the routing of urban logistics by context-based social network and multi-criteria decision analysis. Symmetry, 14(9).
Zhang, D.-G., Wang, J.-X., Zhang, J., Zhang, T., Yang, C., and Jiang, K.-W. (2022). A new method of fuzzy multicriteria routing in vehicle ad hoc network. IEEE Transactions on Computational Social Systems, pages 1-13.
Bibri, S. E. and Krogstie, J. (2020). The emerging data-driven smart city and its innovative applied solutions for sustainability: The cases of london and barcelona. Energy Informatics, 3:1-42.
Brito, M., Santos, C., Oliveira, H., Cerqueira, E., and Rosário, D. (2022). Air pollution calculation for location based social networks multimodal routing service. In VI Workshop de Computação Urbana, pages 280-293. SBC.
Han, X., Hu, X., Wu, H., Shen, B., and Wu, J. (2020). Risk prediction of theft crimes in urban communities: An integrated model of lstm and st-gcn. IEEE Access, 8:217222-217230.
HERE (2023). Build apps with here maps api and sdk platform access: Here developer.
Hsieh, H.-P. and Lin, F. (2022). Recommending taxi routes with an advance reservation - a multi-criteria route planner. International Journal of Urban Sciences, 26(1):162-183.
Kaivonen, S. and Ngai, E. C.-H. (2020). Real-time air pollution monitoring with sensors on city bus. Digital Communications and Networks, 6(1):23-30.
Kelly, F. J. and Kelly, J. (2009). London air quality: a real world experiment in progress. Biomarkers, 14(sup1):5-11. PMID: 19604051.
Legaspi, J., Bhada, S. V., Mathisen, P., and DeWinter, J. (2020). Smart city transportation: A multidisciplinary literature review. In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 957-964.
Liu, D., Tang, J., and Zhang, C. (2019). Application of data analysis in trend prediction of different crime types in london. In Mao, R., Wang, H., Xie, X., and Lu, Z., editors, Data Science, pages 445-467, Singapore. Springer Singapore.
Nguyen, D. C., Ding, M., Pathirana, P. N., Seneviratne, A., Li, J., Niyato, D., Dobre, O., and Poor, H. V. (2022). 6g internet of things: A comprehensive survey. IEEE Internet of Things Journal, 9(1):359-383.
OpenStreetMap, c. (2017). Planet dump retrieved from https://www.openstreetmap.org.
Rodrigues, L. S., Sammarco, M., Detyniecki, M., and Campista, M. E. M. (2021). CRAWDAD dataset ufrj/london-trajectories (v. 2021-03-22). Downloaded from https://crawdad.org/ufrj/london-trajectories/2021-03-22.
Saaty, T. L. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1):9-26. Desicion making by the analytic hierarchy process: Theory and applications.
Sarraf, R. and McGuire, M. P. (2020). Integration and comparison of multi-criteria decision making methods in safe route planner. Expert Systems with Applications, 154:113399.
Savithramma, R. M., Ashwini, B. P., and Sumathi, R. (2022). Smart mobility implementation in smart cities: A comprehensive review on state-of-art technologies. In 2022 4th International Conference on Smart Systems and Inventive Technology (ICSSIT), pages 10-17.
Solé, L., Sammarco, M., Detyniecki, M., and M. Campista, M. E. (2022). Towards drivers' safety with multi-criteria car navigation systems. Future Gener. Comput. Syst., 135(C):1-9.
Wu, M.-Y., Ke, C.-K., and Lai, S.-C. (2022). Optimizing the routing of urban logistics by context-based social network and multi-criteria decision analysis. Symmetry, 14(9).
Zhang, D.-G., Wang, J.-X., Zhang, J., Zhang, T., Yang, C., and Jiang, K.-W. (2022). A new method of fuzzy multicriteria routing in vehicle ad hoc network. IEEE Transactions on Computational Social Systems, pages 1-13.
Publicado
22/05/2023
Como Citar
BRITO, Matheus et al.
Personalized Experience-aware Multi-criteria Route Selection for Smart Mobility. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 41. , 2023, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 504-517.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2023.513.
