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FLSWM 2040 Traffic Projection
Hongbo Chi
Introduction
• FLSWM provides travel forecasting over the entire state reflecting long range demographic and socioeconomic growth.
• It requires additional procedure to validate the model according to the observed traffic count data.
Methodology Framework
Base Year Scenario
Year 2040 Scenario
OD Matrix Estimation
Growth Factor Method
Adjusted 2040 OD Matrix
Adjusted 2040 traffic volume
The Applications Added to FLSWM
OD Matrix Estimation• Cube Analyst 2 is used
Start
Highway Assignment
Extract ICP files
OD Estimation
Obj
End
Update OD matrix
Convergent
A: the route choice probability matrix (ICP files). X: the OD matrix to be estimated. b: the observed traffic count vector.X0: the initial OD matrix. F,G: weighting factors.
OD Matrix Estimation ResultITR
RMSE% for Different Volume Ranges
Over all [20000,Inf] [10000,20000] [5000,10000] [0,5000]1 35.10% 25.00% 35.20% 36.00% 77.70%2 27.20% 19.50% 26.30% 29.40% 67.90%3 24.50% 17.50% 23.50% 27.40% 61.20%4 22.10% 15.80% 21.00% 25.60% 54.70%5 20.20% 14.60% 19.20% 23.90% 48.20%6 18.80% 13.40% 17.90% 22.90% 43.40%
Growth Factor Method
• A simple method to calibrate the future year OD matrix:
OD40calibrated=OD05calibrated+(OD40-OD05)
Model setting
• The model selection for base year scenario
• The model selection for 2040 scenario
Requirement for Computer
• The recommended configuration for computer– CPU: Intel (R), 2 Quad CPU 2.4 GHZ– Memory: 8 GB memory
• The model running time– Base year: 70 hours– Year 2040: 2 hours