Estudio de la serie espacio-temporal de los accidentes de tráfico en la ciudad de Madrid entre 2019 y 2023
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2024
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20/06/2024
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La red viaria de la ciudad de Madrid está formada por 9.371 viales vigentes, los cuales se tramifican hasta llegar a las 64.384 unidades, en los cuales, entre 2019 y 2023, se produjeron 221.786 accidentes de tráfico. Lo que implica que este fenómeno genera unas pautas de localización y patrones espacio-temporales en el municipio. Pudiendo fundamentarse en que la intensidad media del tráfico urbano, durante el año 2022, en días laborales, fue de 1.848.772. Además, el parque de vehículos existente es igual a 1.392.864 turismos, lo que implica que en Madrid hay un 1,29 vehículos por cada hogar. Así pues, la redacción del marco teórico ha servido para tener un conocimiento previo de la materia y analizar posibles desarrollos temáticos dentro de la misma. Mediante el desarrollo de los diferentes apartados que componen el capítulo de resultados, se han detallado las pautas de localización, los patrones espacio-temporales, así como la previsión en la serie temporal de los accidentes de tráfico, y por último, el entrenamiento y modelado predictivo con Inteligencia Artificial de la serie temporal de los accidentes de tráfico. Todo ello, con la finalidad de analizar la distribución espacio-temporal de los accidentes de tráfico en la ciudad de Madrid entre 2019 y 2023.
The road network of the city of Madrid is made up of 9.371 roads in force, which are processed to reach 64.384 units, in which, between 2019 and 2023, 221.786 traffic accidents occurred. This implies that this phenomenon generates location patterns and spatial-temporal patterns in the municipality. Which can be based on the fact that the average intensity of urban traffic during the year 2022, on working days, was 1.848.772. Furthermore, the existing vehicle fleet is equal to 1.392.864 cars, which implies that in Madrid there are 1.29 vehicles for every household. Thus, the drafting of the theoretical framework has served to gain prior knowledge of the subject and to analyse possible thematic developments within it. Through the development of the different sections that make up the results chapter, we have detailed the localisation patterns, the spatio-temporal patterns, as well as the prediction in the time series of traffic accidents, and finally, the training and predictive modelling with Artificial Intelligence of the time series of traffic accidents. All this with, the aim of analysing the spatio-temporal distribution of traffic accidents in the city of Madrid between 2019 and 2023.
The road network of the city of Madrid is made up of 9.371 roads in force, which are processed to reach 64.384 units, in which, between 2019 and 2023, 221.786 traffic accidents occurred. This implies that this phenomenon generates location patterns and spatial-temporal patterns in the municipality. Which can be based on the fact that the average intensity of urban traffic during the year 2022, on working days, was 1.848.772. Furthermore, the existing vehicle fleet is equal to 1.392.864 cars, which implies that in Madrid there are 1.29 vehicles for every household. Thus, the drafting of the theoretical framework has served to gain prior knowledge of the subject and to analyse possible thematic developments within it. Through the development of the different sections that make up the results chapter, we have detailed the localisation patterns, the spatio-temporal patterns, as well as the prediction in the time series of traffic accidents, and finally, the training and predictive modelling with Artificial Intelligence of the time series of traffic accidents. All this with, the aim of analysing the spatio-temporal distribution of traffic accidents in the city of Madrid between 2019 and 2023.