Urban Traffic Congestion Prediction: A Multi-Step Approach Utilizing Sensor Data and Weather Information
Nikolaos Tsalikidis,
Aristeidis Mystakidis,
Paraskevas Koukaras
et al.
Abstract:The continuous growth of urban populations has led to the persistent problem of traffic congestion, which imposes adverse effects on quality of life, such as commute times, road safety, and the local air quality. Advancements in Internet of Things (IoT) sensor technology have contributed to a plethora of new data streams regarding traffic conditions. Therefore, the recognition and prediction of traffic congestion patterns utilizing such data have become crucial. To that end, the integration of Machine Learning… Show more
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