Estimation of Missing Left Turning Movement For Intersections Traffic Volume Count
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Abstract
Intersection traffic volume count must be in of the accurate data, because it is a crucial in the calibration and validation of traffic demand models. It is process in a continuous manner done by the analyst, planner or designer. Many procedures were recently produced to estimate the intersection turning movement matrix. Sometimes, these procedures of traffic volume count may have unusual, unavailable or missing values especially for the left turn movement, which is more effective in capacity analysis. Typical four mathematical and statistical methods of estimating the missing left turn movement volume were developed for about twenty signalized intersections. The most significant one is the typical curve estimation method. It is a power curve and in a simple formula compared with several other imputation techniques. This method can be superior to substitute the other methods in estimating the intersection traffic volume matrices.
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References
Federal Highway Administration, USDoT, “Safety Effectiveness of Intersection Left – and Right -Turn Lanes“,Tech Brief, FHWA–02-103 Nov.(2002).
Zhao, Fang and Chung, Soon, “Estimation of Annual Average Daily Traffic in a Florida County Using GIS and Regression “TRB 1-3440, (2001).
Gothe, Maud Brenninger, Jornsten, Kurt O. and Lundgren, Jan T., “Estimation of Origin – Destination Matrices from Traffic Counts Using Multi-objective Programming Formulations” Transpn. Res.-B, Vol.23B, No.4, (1989), pp 257– 269. DOI: https://doi.org/10.1016/0191-2615(89)90028-3
Willumsen, Luis G., “Estimation of O – D Matrices form Traffic Counts” presentation at PTRC Course on 19-21, March (1986).
Ferlis, R.A. ; Bowman, L.A. and Cima, B.T. ,“ Guide to Urban Traffic Volume Counting” Federal Highway Administration, US Department of Transportation, Urban Planning Division, Final Report, February (1980).
Woodruff, Stephen M, “Model Based Estimation of Covariance Matrices with Applications to the EM-Algorithm “ Bureau of Labor Statistics, 441 G St. N.W., Washington D.C. , (1990).
Sclove, Stan ,“ A Beginner’s Guide to Structural Equation Modeling” 2nd ed. , University of Illinois at Chicago , College of Business Administration, Department of Information & Decision Sciences, Feb (2005).
Pedersen, N. J., and D. R. Samdahl , “ Highway Traffic Data for Urbanized Area Project Planning and Design” NCHRP Report 255, National Research Council, TRB, Washington, D.C., (1982) , pp. 102-114.
Gerken, Jeff and Meyers, Dan ,“A Practical Approach to Managing Intersection Traffic Data for Large Scale Studies “ Mid-Continent Transportation Symposium Proceedings, (2000).
Taylor, M.A.P. & Young, W.(TRAFFICA NALYSIS–NEW TECHNOLOGY & NEW SOLUTIONS) , HARGCCN, Victoria (1988), pp. 304-320.
Al-Badri, A. H. , “ Improvement of Traffic Flow in Samarra City ” Msc. thesis, University of Tikrit, College of Engineering , (1997).
Transportation Research Board, National Research Council (HIGHWAY CAPACITY MANUAL) S.R. HRB 209 TR, (2000). ch.10
Hicks, Charles R., “ FUNDAMENTAL CONCEPTS IN THE DESIGN OF EXPERIMENTS “ Arabic translation by Kammas, K.S. , University of Mustanserria , (1984) , pp.91-96.
Aldrin, Magne , “ The Basic Curve Method for Traffic Volume Estimation “ , Norwegian Computing Center , Blindern (2004).