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A system for traffic data mining and traffic monitoring over city road networks

Stamatopoulos Konstantinos

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Summary

In recent years, the issue of traffic congestion has been steadily increasing, making driving an arduous and unfavorable experience for many of us. Despite the expansion of metropolitan areas, an effective solution to the continuously growing number of vehicles in their road networks has yet to be found. In response to this challenge, we have embarked on the design of an application that simulates traffic flow in the city of Chania, serving as a support system for traffic decision-making.Our approach involves collecting real-time traffic data at intervals of a few minutes for each edge/road segment in the city. Subsequently, we employ a divisive hierarchical clustering model to cluster this data, extracting relationships among them, such as traffic propagation, split, and merge. This process enables us to illustrate the behavior of the road network’s traffic flow throughout the day, providing a valuable tool for developing improved transportation systems and techniques to alleviate road overloading.

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