Identification of variables influencing the origin of traffic congestion points

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Abstract
The identification of variables triggering traffic congestion points in cities has been revealed as an extraordinarily complex task, involving characterization, prediction, and forecasting activities of traffic congestion points. The exhaustive literature review indicates that key factors influencing urban traffic congestion include traffic incidents, road infrastructure conditions, the day of the week, time of day, the month, workweeks, and vacation periods. However, there is a lack of quantitative representations of traffic that allows us to accurately assess the degree of influence of relevant traffic variables such as incidents and service locations in the generation of traffic congestion points. In this context, the main objective of this research work focuses on identifying the most significant variables causing traffic congestion points through the use of mathematical techniques. This aims to contribute to the development of models for mitigating traffic congestion. The case study of traffic, incidents, and services in Mexico City is used in this work.

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