Abstract
The problem of travel time estimation by neural nets based on traffic data is considered in the paper. After a successful preliminary research on using neural networks to predict travel time based on real data is recalled, the next step of our research is presented, which utilizes urban traffic simulations in SUMO simulator as training data generator for training neural networks.
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This work was partially supported from grant no 0401/0114/16 at Wrocław University of Science and Technology.
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Ciskowski, P., Drzewiński, G., Bazan, M., Janiczek, T. (2019). Estimation of Travel Time in the City Using Neural Networks Trained with Simulated Urban Traffic Data. In: Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J. (eds) Contemporary Complex Systems and Their Dependability. DepCoS-RELCOMEX 2018. Advances in Intelligent Systems and Computing, vol 761. Springer, Cham. https://doi.org/10.1007/978-3-319-91446-6_13
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DOI: https://doi.org/10.1007/978-3-319-91446-6_13
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