Content area
Traffic congestion in urban areas is a complex phenomenon influenced by various factors. The location of essential city services such as hospitals, schools, shopping centers, and workplaces plays a crucial role in generating vehicular congestion. Additionally, events like traffic accidents, ongoing constructions, adverse weather conditions, and other incidents can have a significant impact on traffic congestion. The representation of traffic congestion through a mathematical model that takes into account the distances be-tween the location of services and traffic incidents makes it possible to characterize the dynamic state of congestion in specific city locations. The contribution of this research is the development of a model that characterizes the level of congestion based on the proximity of city services and traffic events. The proposed mathematical model provides a valuable tool for effectively addressing and mitigating congestion and also enables informed decision making and proactive actions to improve urban mobility.
Details
Datasets;
Workplaces;
Infrastructure;
Mathematical models;
Urban planning;
Multiple criterion;
Roads & highways;
Maps;
Population density;
Variables;
Data analysis;
Data collection;
Shopping centers;
Gross Domestic Product--GDP;
Weather;
Traffic congestion;
Economic growth;
Cities;
Representations;
Case studies;
Urban areas