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- W2945131323 abstract "Intelligent Transportation Systems have become a necessity with the increasing number of cars running, especially in the urban roads. This paper presents a novel system capable to forecast the traffic in the urban road networks. This study aims to analyze the traffic patterns based on Floating Car Data using a supervised learning approach. The prediction of the mean travel time and the mean waiting time is used to evaluate the proposed method with the R-Square evaluation metric for Lasso and residuals. We also evaluate the prediction performance when we reduce the number of connected vehicles. Based on these evaluations, the proposed system can forecasts well the traffic conditions in the urban road networks with a good accuracy, only with 10% of connected vehicles. Such a system presents a technical means for the road managers to better understand the travel patterns and helps authorities to make a strategic decisions." @default.
- W2945131323 created "2019-05-29" @default.
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- W2945131323 date "2019-01-01" @default.
- W2945131323 modified "2023-09-23" @default.
- W2945131323 title "A Novel Traffic Prediction System based on Floating Car Data and Machine Learning" @default.
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- W2945131323 doi "https://doi.org/10.1145/3320326.3320355" @default.
- W2945131323 hasPublicationYear "2019" @default.
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