Matching Hourly,Daily,and Monthly Traffic Patterns to Estimate Missing Volume Data

Abstract

Missing values are an important issue for traffic data programs and lead to difficulties in data analyses and application. Previous research accurately imputed missing hourly volumes of a range from a few days up to one and a half weeks for various types of traffic counts. However, imputation errors of the applied hourly models increase dramatically after some reliable imputing periods; this indicates their limitations in real applications. Therefore, this study investigates pattern-matching algorithms to fill large missing data intervals. The algorithms use historical data to develop a series of candidate patterns and compare them to patterns with missing data. Data from the best-fit pattern is then used to estimate the missing data. The algorithms show improved accuracy over traditional models used in practice and prove suitable to impute missing hourly, daily, and monthly traffic volume data.

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References

Liu

G. X.

Sharma

S. C.

and Luo

J. Z.

Traffic Data Needs for Saskatchewan Highways and Transportation. Research Report of Saskatchewan Highways and Transportation. Regina, Saskatchewan, Canada, June 2001.

Garber

N. J.

and Hoel

L. A.

Traffic and Highway Engineering. West Publishing Company, New York, 1988.

Guidelines for Traffic Data Programs. AASHTO, Washington, D.C., 1992.

Zhong

Sharma

S. C.

and Liu

Z. B.

Studying the Counting Efficiency of Continuous Traffic Monitoring Programs. Proc., 32nd Annual Congress of the Canadian Society of Civil Engineering, Saskatoon, Saskatchewan, Canada, 2004.

Zhong

Sharma

S. C.

and Lingras

Rationalizing Reliable Imputation Durations of Genetically Designed Models Based on Alberta Roads. Proc., 2005 Annual Conference of the Canadian Society for Civil Engineering, June 2005.

1990 Survey of Traffic Monitoring Practices among State Transportation Agencies of the United States. Report No. FHWA-HRP-NM-90-05. New Mexico State Highway and Transportation Department, Santa Fe, Dec. 1990.

Albright

An Imperative for, and Current Progress toward, National Traffic Monitoring Standards. ITE Journal, Vol. 61, No. 6 1991, pp. 23–26.

Redfern

E. J.

Watson

S. M.

Tight

M. R.

and Clark

S. D.

A Comparative Assessment of Current and New Techniques for Detecting Outliers and Estimating Missing Values in Transport Related Time Series Data. Proc., Highways and Planning Summer Annual Meeting of the Institute of Science and Technology, University of Manchester, United Kingdom, Sept. 1993.

FHWA's Scanning Program. FHWA Study Tour for European Traffic Monitoring Programs and Technologies. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C., Aug. 1997.

10.

Little

R. A.

and Rubin

D. B.

Statistical Analysis with Missing Data. Wiley, New York, 1987.

11.

Clark

S. D.

Application of Outlier Detection and Missing Value Replacement Techniques to Various Forms of Traffic Count Data. ITS Working Paper 384. University of Leeds, United Kingdom, 1992.

12.

Watson

S. M.

Clark

S. D.

Redfern

E. J.

and Tight

M. R.

Outlier Detection and Missing Value Estimation in Time Series Traffic Count Data. Proc., 6th World Conference on Transportation Research, Vol. II, 1993, pp. 1151–1162.

13.

Nihan

N. L.

and Holmesland

K. O.

Use of the Box and Jenkins Time Series Technique in Traffic Forecasting. Transportation, Vol. 9, 1980, pp. 125–143.

14.

Harvey

A. C.

and Pierse

R. G.

Estimating Missing Observations in Economic Time Series. Journal of American Statistical Association, Vol. 79, No. 385, 1984.

15.

Box

and Jenkins

Time Series Analysis: Forecasting and Control. Holden-Day, San Francisco, Calif., 1970.

16.

Chatfield

The Analysis of Time Series: An Introduction, 3rd ed. Chapman and Hall Ltd., London, 1984.

17.

Sharma

S. C.

and Werner

Improved Method of Grouping Province-wide Permanent Traffic Counters. In Transportation Research Record 815, TRB, National Research Council, Washington, D.C., 1981, pp. 12–18.

18.

Sharma

S. C.

and Allipuram

Duration and Frequency of Seasonal Traffic Counts. Journal of Transportation Engineering, Vol. 119, No. 3, May–June 1993, pp. 344–359.