01336928

Component

https://doi.org/10.3141/2260-03

http://scholar.google.com...lson&publication_year=2011

Research investigated ways to forecast traffic flow over an area covering multiple links of a roadway network. The question arose of whether to construct one large-scale model or to combine results from separate smaller-scale models. Intuition favors link-specific analyses, but econometric results show how using aggregate models can increase accuracy. It is shown how theory holds that correlations between traffic conditions on different roadway links and errors in link-specific observations of traffic conditions increase the relative accuracy of larger-scale models, whereas site-specific sensitivities suggest smaller-scale data. Empirical evidence is presented regarding the relative accuracy of various models of traffic flow rate. One form of a seasonal autoregressive integrated moving average time series model for general flow forecasting is chosen, along with methodologies for automatically selecting models based on input data. Studies based on data from the Tokyo Metropolitan Expressway show that increasing data aggregation consistently increases model accuracy. Sums of forecasts of link flows yield predictions of areawide flow roughly as accurate as predictions based on univariate analysis of areawide data. Areawide flows are easier to predict accurately than link flows. Modeling large-area traffic flow with a univariate model is considerably simpler but produces less subsequently useful results than use of separate, link-specific models.

01362482

11-0670

English

pp 16-23

2011

Transportation Research Record: Journal of the Transportation Research Board

9780309222976

Print

Figures (5) ; References (19) ; Tables (2)

Accuracy; Econometric models; Network links; Traffic data; Traffic flow; Traffic forecasting; Traffic models

Data aggregation

Tokyo Metropolitan Expressway (Japan)

Autoregressive integrated moving average models

Tokyo (Japan)

Highways; Operations and Traffic Management; Planning and Forecasting; I71: Traffic Theory

TRIS, TRB

Feb 17 2011 5:31PM

• Alternative Definitions of Passing Critical Gaps
• Comparing Heavy Vehicle and Passenger Car Lane-Changing Maneuvers on Arterial Roads and Freeways
• Development of Extreme Value Distribution Method for Estimation of Expressway Capacity
• Empirical Analysis of Effects of Automated Section Speed Enforcement System on Traffic Flow at Freeway Bottlenecks
• Empirical Study of Impact of Icy Roadway Surface Condition on Driver Car-Following Behavior
• Estimating Acceleration, Fuel Consumption, and Emissions from Macroscopic Traffic Flow Data
• Fundamental Diagram of Traffic Flow: New Identification Scheme and Further Evidence from Empirical Data
• General Newell Model and Related Second-Order Expressions
• Low-Rank Unscented Kalman Filter for Freeway Traffic Estimation Problems
• Macroscopic Fundamental Diagrams for Freeway Networks: Theory and Observation
• Modeling of Travel Time Variations on Urban Links in London
• Multiregime Sequential Risk-Taking Model of Car-Following Behavior: Specification, Calibration, and Sensitivity Analysis
• Real-Time Solution of Velocity-Based First-Order Continuum Traffic Model with Finite Element Method
• Use of Skew-Normal and Skew-t Distributions for Mixture Modeling of Freeway Speed Data
• Variations in Parameters of Time Headway Models According to Macroscopic Variables, Fundamental Diagram, and Exogenous Effects
• Wiedemann Revisited: New Trajectory Filtering Technique and Its Implications for Car-Following Modeling