Empirical Freeway Queuing Duration Model
Publication: Journal of Transportation Engineering
Volume 127, Issue 1
Abstract
An empirical, three-regime, freeway queuing duration model is developed from a database of 161 observations. The explanatory variable is the ratio of the annual average daily traffic volume to hourly capacity (AADT/C). The daily recurring queuing duration, in hours, is estimated to within 0.5 h of the actual at 51% of the 161 observations. The model potentially represents an improvement to the volume-delay function traditionally used in traffic assignment, because the entire peak period, not just the peak hour, is considered. The model may be useful where resources prevent the direct measurement of recurring congestion. The model's form may be considered for application in real-time traffic management. A residuals analysis indicates recommendations for model improvement, including additional explanatory variable, a larger database, careful identification of bottlenecks, circumstantial freeway capacity calculations, consideration for the day-to-day variability of recurring congestion, and nonlinear regression.
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References
1.
Allen, W. G., Jr. ( 1991). “Analysis of corridor traffic peaking.” Transp. Res. Rec. 1305, Transportation Research Board, Washington, D.C., 50–60.
2.
American Association of State Highway and Transportation Officials (AASHTO). ( 1990). A policy on geometric design of highways and streets, Washington, D.C.
3.
Archdeacon, T. J. ( 1994). Correlation and regression analysis: A historian's guide, University of Wisconsin Press, Madison, Wis.
4.
Banks, J. H. ( 1990). “Flow processes at a freeway bottleneck.” Transp. Res. Rec. 1287, Transportation Research Board, Washington, D.C., 20–28.
5.
Banks, J. H. ( 1991). “The two-capacity phenomenon: some theoretical issues.” Transp. Res. Rec. 1320, Transportation Research Board, Washington, D.C., 234–241.
6.
Borden, J. ( 1993). HICOMP report: statewide highway congestion monitoring program, Operational Sys. Branch, Ofc. of Hwy. and Toll Bridge Operations, Div. of Traffic Operations, California Department of Transportation, Sacramento, Calif.
7.
Borland Quattro Pro for Window user's guide: version 5.0. (1993). Borland International, Scotts Valley, Calif.
8.
Branston, D. ( 1976). “Link capacity functions: A review.” Transp. Res., 10, 223–236.
9.
COMSIS. ( 1996). “Development of diurnal traffic distribution and daily, peak, and offpeak vehicle speed estimation procedures for air quality planning.” Final Rep. B-94-06, Federal Highway Administration, Washington, D.C.
10.
Cottrell, W. D. ( 1988). “Determining who should pay for urban traffic congestion: case study of Boston's Central Artery/Third Harbor Tunnel project.” Civil Engineer's Degree dissertation, Massachusetts Institute of Technology, Cambridge, Mass.
11.
Cottrell, W. D. ( 1997). “Development of a set of measures and two surrogate models of recurring freeway congestion.” PhD dissertation, Dept. of Civ. and Envir. Engrg., University of Utah, Salt Lake City.
12.
Cottrell, W. D. ( 1998). “Estimating the probability of recurring freeway congestion.” Transp. Res. Rec. 1634, Transportation Research Board, Washington, D.C., 19–27.
13.
Drummond, J., and Polus, A. ( 1991). Evaluation of congestion trends on Chicago area expressways: 1980–1989, K&D Facilities Resource Corp., Chicago.
14.
Edie, L. C., and Foote, R. S. ( 1960). “Effect of shock waves on tunnel traffic flow.” Proc., Hwy. Res. Board, Highway Research Board, Washington, D.C., 39, 492–505.
15.
Elefteriadou, L., Roess, R. P., and McShane, W. R. ( 1995). “Probabilistic nature of breakdown at freeway-merge junctions.” Transp. Res. Rec. 1484, Transportation Research Board, Washington, D.C., 80–89.
16.
Epps, A., Cheng, J. C., and May, A. D. ( 1994). “Developing methodologies for quantifying congestion delay.” Res. Rep. UCB-ITS-RR-94-2, Inst. of Transp. Studies, University of California, Berkeley, Calif.
17.
Forsythe, A. B. ( 1972). “Robust estimation of straight line regression coefficients by minimizing pth power deviations.” Technometrics, 11(1), 159–166.
18.
HICOMP report: Highway Congestion Monitoring Program. (1994). Ofc. of Hwy. Operations, California Department of Transportation, Oakland, Calif.
19.
Highway capacity manual. (1994). 3rd Ed., Transportation Research Board, Washington, D.C.
20.
Kurth, D. L., van den Hout, A., and Ives, B. ( 1996). “Implementation of highway capacity manual-based volume-delay functions in regional traffic assignment process.” Transp. Res. Rec. 1556, Transportation Research Board, Washington, D.C., 27–36.
21.
Larsson, T., and Patriksson, M. ( 1995). “An augmented Lagrangean dual algorithm for link capacity side constrained traffic assignment problems.” Transp. Res.-B, 29(6), 433–455.
22.
Lisco, T. W. ( 1983). “A procedure for predicting queues and delays on expressways in urban core areas.” CTPS Tech. Report 36, Central Transportation Planning Staff, Boston.
23.
Lomax, T. J., Turner, S., Levinson, H. S., Pratt, R. H., Bay, P. N., and Douglas, G. B. ( 1996). “Quantifying congestion.” NCHRP Rep. 398, Texas A&M Res. Found., Texas Transportation Institute, College Station, Tex.
24.
Loudon, W. R., Ruiter, E. R., and Schlappi, M. L. ( 1989). “Predicting peak-spreading under congested conditions.” Transp. Res. Rec. 1203, Transportation Research Board, Washington, D.C., 1–9.
25.
Mallows, C. L. ( 1980). “Some theory of nonlinear smoothers.” The Annals of Statistics, 8(4), 695–715.
26.
“Management and monitoring systems: interim final rule. II: Department of Transportation, Federal Highway Administration, 23 CFR Parts 500 and 626, and Federal Transit Administration, 49 CFR Part 614.” Federal Register, December 1.
27.
McShane, W. R., Roess, R. P., and Prassas, E. S. ( 1998). Traffic engineering, 2nd Ed., Prentice-Hall, Upper Saddle River, N.J.
28.
Microsoft Excel/Visual Basic programmer's guide. (1995). Microsoft Corporation, Microsoft Press, Redmond, Wash.
29.
Mosteller, F., and Tukey, J. W. ( 1977). Data analysis and regression: a second course in statistics, Addison-Wesley, Reading, Mass.
30.
Pindyck, R. S., and Rubinfeld, D. L. ( 1981). Econometric models and economic forecasts, 2nd Ed., McGraw-Hill, New York.
31.
Pisarki, A. ( 1990). “Summary of the recommendations of the workshop on national urban congestion monitoring.” Rep. No. FHWA-PL-90-029, Ofc. of Hwy. Information Mgmt., Federal Highway Administration, Washington, D.C.
32.
Powell, J. L. ( 1983). “Least absolute deviations estimation for the censored regression model.” J. Econometrics, 25, 303–325.
33.
Ratkowsky, D. A. ( 1990). Handbook of nonlinear regression models, Marcel Dekker, New York.
34.
San Diego Association of Governments (SANDAG). ( 1988). “Freeway peak-hours congestion.” SANDAG Info No. 6, San Diego.
35.
Sposito, V. A. ( 1989). Linear programming with statistical applications, Iowa State University Press, Ames, Iowa.
36.
Thorndike, R.M. ( 1978). Correlational procedures for research, Gardner Press, New York.
37.
Thurgood, G. S., Cabell, L., Christensen, R. C., Taylor, T. J., Schultz, G. G., and Walker, B. P. ( 1994). “Strategies to reduce recurring interstate congestion: appendices A-E.” Rep. No. UT-94.06A, Civ. and Envir. Engrg. Dept., Brigham Young University, Provo, Utah.
38.
Thurgood, G. S., and Taylor, T. J. ( 1994). “Strategies to reduce recurring interstate congestion: a freeway congestion index (FCI).” Rep. No. UT-94.06, Civ. and Envir. Engrg. Dept., Brigham University, Provo, Utah.
39.
Traffic assignment manual. (1964). Urban Plng. Div., Bureau of Public Roads, U.S. Department of Commerce, Washington, D.C.
40.
Tukey, J. W. ( 1977). Exploratory data analysis, Addison-Wesley, Reading, Mass.
41.
Turner, S. M., Lomax, T. J., and Levinson, H. S. ( 1996). “Measuring and estimating congestion using travel-time based procedures.” Transp. Res. Rec. 1564, Transportation Research Board, Washington, D.C.
42.
van Toorenburg, J. A. C. ( 1991). “Performance of motorways and trunk routes at high traffic volume.” Proc., Int. Symp. on Hwy. Capacity: Hwy. Capacity and Level of Service, Balkema, Rotterdam, The Netherlands, 413–418.
43.
Velleman, P. F. ( 1980). “Definition and comparison of robust nonlinear data smoothing algorithms.” J. Am. Statistical Assoc., 75(371), 609–615.
44.
Watson, C. J., Billingsley, P., Croft, D. J., and Huntsberger, D. V. ( 1993). Statistics of management and economics, Allyn and Bacon, Needham Heights, Mass.
Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 127 • Issue 1 • February 2001
Pages: 13 - 20
History
Received: Feb 22, 2000
Published online: Feb 1, 2001
Published in print: Feb 2001
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