Map Matching for the public transport network in Xalapa City / Map Matching para a rede de transportes públicos na Cidade de Xalapa
DOI:
https://doi.org/10.34117/bjdv8n5-586Keywords:
global positioning system, graph theory, matching pursuit algorithms, mathematical modelling.Abstract
In Xalapa, Veracruz, Mexico, there was not a correct description of the more than 100 public transport bus routes that existed, for which a collective event was held to collect Global Positioning System locations. The trajectories obtained were not adjusted to the layout of the city's public road network, due to measurement errors caused by the variety of devices used for tracking. To recover the correct trajectories, a Map Matching algorithm was used based on the optimization of paths in graphs whose nodes belong to the public roads of the city. This work presents the description of the data collection methodology and the construction of the graphs for the implementation of the algorithm that finally recovered the real routes.
References
M. Kubicka, A. Cela, H. Mounier, and S.-I. Niculescu, “Comparative Study and Application-Oriented Classification of Vehicular Map-Matching Methods,” IEEE Intell. Transp. Syst. Mag., vol. 10, no. 2, pp. 150–166, 2018, doi: 10.1109/MITS.2018.2806630
M. A. Quddus, W. Y. Ochieng, L. Zhao, and R. B. Noland, “A general map matching algorithm for transport telematics applications,” GPS Solut., vol. 7, no. 3, pp. 157–167, Dec. 2003, doi: 10.1007/s10291-003-0069-z
H. Koller, P. Widhalm, M. Dragaschnig, and A. Graser, “Fast Hidden Markov Model Map-Matching for Sparse and Noisy Trajectories,” in 2015 IEEE 18th International Conference on Intelligent Transportation Systems, Sep. 2015, pp. 2557–2561, doi: 10.1109/ITSC.2015.411
Instituto Nacional de Estadística y Geografía (INEGI), Principales resultados de la Encuesta Inercensal 2015 Estados Unidos Mexicanos. México: Instituto Nacional de Estadística y Geografía, 2015.
Instituto Nacional de Estadística y Geografía (INEGI), Principales resultados de la Encuesta Intercensal 2015. Veracruz de Ignacion de la Llave. México: Instituto Nacional de Estadística y Geografía, 2016.
Instituto Nacional de Estadística y Geografía (INEGI), Anuario estadístico y geográfico de Veracruz de Ignacio de la Llave 2016. México: Instituto Nacional de Estadística y Geografía, 2016.
Codeando Xalapa, “Guía Metodológica Mapatón Ciudadano.Org,” 2018. [Online]. Available: https://www.mapaton.org.
P. Newson and J. Krumm, “Hidden Markov map matching through noise and sparseness,” in Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems - GIS ’09, 2009, p. 336, doi: 10.1145/1653771.1653818