Implications of Spatiotemporal Data Aggregation on Short-Term Traffic Prediction Using Machine Learning Algorithms

<div>Ranking of attributes in terms of their relative importance to the performance of SVR models, for three different input data aggregation levels (segment 23). The plots for the volume features are on the left and those for the occupancy features are on the right. (a) 30 sec aggregation level. (b) 5 min aggregation level. (c) 15 min aggregation level.</div>

Journal of Advanced Transportation

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Figure 9

Figure 9: Implications of Spatiotemporal Data Aggregation on Short-Term Traffic Prediction Using Machine Learning Algorithms 