Predicting vehicle fuel consumption patterns using floating vehicle data

doi:10.1016/j.jes.2017.03.008

Predicting vehicle fuel consumption patterns using floating vehicle data

2017-09-01

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DOI：10.1016/j.jes.2017.03.008

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The status of energy consumption and air pollution in China is serious. It is important to analyze and predict the different fuel consumption of various types of vehicles under different influence factors. In order to fully describe the relationship between fuel consumption and the impact factors, massive amounts of floating vehicle data were used. The fuel consumption pattern and congestion pattern based on large samples of historical floating vehicle data were explored, drivers' information and vehicles' parameters from different group classification were probed, and the average velocity and average fuel consumption in the temporal dimension and spatial dimension were analyzed respectively. The fuel consumption forecasting model was established by using a Back Propagation Neural Network. Part of the sample set was used to train the forecasting model and the remaining part of the sample set was used as input to the forecasting model. (C) 2017 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.

Keywords:

Vehicle fuel consumption

Prediction

Floating vehicle data

Predicting vehicle fuel consumption patterns using floating vehicle data

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