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Erschienen in:

16.10.2024

Advanced Modeling and Interpretation for Accurate Intersection Traffic Time Prediction

verfasst von: Deepika, Gitanjali Pandove

Erschienen in: International Journal of Intelligent Transportation Systems Research | Ausgabe 3/2024

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Abstract

This study presents the results for predicting waiting time of vehicles at intersections. Various traditional models (LR, DT, RF, GB, KNN, MLP, SVM) and H2O-SEM approach are compared based on Mean Square Error (MSE), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and coefficient of determination. Additionally, the H2O AutoML module is introduced as an alternative for comparison. The traffic generation and investigation are performed using the SUMO simulator. The findings aim to identify the most effective model for accurate waiting time prediction at intersections.

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Metadaten
Titel
Advanced Modeling and Interpretation for Accurate Intersection Traffic Time Prediction
verfasst von
Deepika
Gitanjali Pandove
Publikationsdatum
16.10.2024
Verlag
Springer US
Erschienen in
International Journal of Intelligent Transportation Systems Research / Ausgabe 3/2024
Print ISSN: 1348-8503
Elektronische ISSN: 1868-8659
DOI
https://doi.org/10.1007/s13177-024-00428-x

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