Journal of Advanced Transportation · 2006 · 28 citations · 9 references
EngineeringAutomotive EngineeringComputer ScienceForecastingTransportationTransportation EngineeringIntelligent Transportation SystemsNavigation SystemsShort-term ForecastingTime Series ForecastingTraffic EngineeringTransport ModellingField Data CollectionKalman Filter PredictionMotion ForecastingPrediction ModelsSpeed PredictionTraffic Speed AnalysisTraffic Speed PredictionTravel Time Prediction
Abstract The objective of this study is the development of the short‐term prediction models to predict average spot speeds of the subject location in the short‐term periods of 5, 10 and 15 minutes respectively. In this study, field data were used to see the comparison of the predictability of Regression Analysis, ARIMA, Kalman Filtering and Neural Network models. These field data were collected from image processing detectors at the urban expressway for 17 hours including both peak and non‐peak hours. Most of the results were reliable, but the results of models using Kalman Filtering and Neural Networks are more accurate and realistic than those of the others.
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Time Series Analysis: Forecasting and Control
Michael D. Geurts, George E. P. Box, Gwilym M. Jenkins · Journal of Marketing Research · 1977 · 19.3K citations
Computing, Data Science, Forecasting +11
Time Series Analysis: Univariate and Multivariate Methods
Alice Z. Chuang, William W. S. Wei · Technometrics · 1991 · 1.3K citations