Comparison of four modeling techniques for short-term AADT forecasting in Hong Kong

Journal of Transportation Engineering

Volumn 129, Issue 3, 2003, Pages 271-277

  Tang, Y F ^a   Lam, William H K ^a   Ng, Pan L P ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Hong Kong; Neural networks; Traffic management; Traffic volume

Indexed keywords

DATABASE SYSTEMS; FORECASTING; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; MAXIMUM LIKELIHOOD ESTIMATION; NEURAL NETWORKS; REGRESSION ANALYSIS; STATISTICAL METHODS;

ANNUAL AVERAGE DAILY TRAFFIC (AADT);

HIGHWAY TRAFFIC CONTROL;

COMPARATIVE STUDY; FORECASTING METHOD; MODELING; PLANNING METHOD; TRAFFIC MANAGEMENT; TRANSPORTATION PLANNING;

CHINA;

EID: 0038630725     PISSN: 0733947X     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)0733-947X(2003)129:3(271)     Document Type: Article

References (14)

1. Ahmed, M. S., and Cook, A. R. (1979). "Analysis of freeway traffic time-series data by using Box-Jenkins techniques." Transportation Research Record 722, Transportation Research Board, Washington, D.C., 1-9.
2. Bowerman, B. L., and O'Connell, R. T. (1987). Time series forecasting-Unified concepts and computer implementation. Duxbury Press, Boston.
3. Davis, G. A., and Nihan, N. L. (1991). "Nonparametric regression and short-term freeway traffic forecasting." J. Transp. Eng., 117(2), 178-188.
4. Dochy, T. M., and Lechevallier, Y. (1995). "Short term traffic forecasting using neural network." Transportation system: Theory and application of advanced technology, B. Liu and J. M. Blosseville, eds., Vol. 2, Pergamon, Oxford, 633-638.
5. Hamed, M. M., Al-Masaeid, H. R., and Bani Said, Z. M. (1995). "Short-term prediction of traffic volume in urban arterials." J. Transp. Eng., 121(3), 249-254.
6. Lam, W. H. K., and Xu, J. (2000). "Estimation of AADT from short period counts in Hong Kong-A comparison between neural network method and regression analysis." J. Adv. Transp., 34(2), 249-268.
7. Lin, W. H. (2001). "A Gaussian maximum likelihood formulation for short-term forecasting of traffic flow." Proc., IEEE Intelligent Transportation System Conf., Institute of Electrical and Electronics Engineers, Oakland, Calif., 152-157.
8. Moorthy, C. K., and Ratcliffe, B. G. (1988). "Short term traffic forecasting using time series methods." Transp. Plan. Technol., 12(1), 45-56.
9. Nihan, N. L., and Holmesland, K. O. (1980). "Use of Box and Jenkins time series technique in traffic forecasting." Transportation, 9(2), 125-143.
10. Smith, B. L., and Demetsky, M. (1994). "Short-term traffic flow prediction: Neural network approach." Transportation Research Record 1453, Transportation Research Board, Washington, D.C., 98-104.
11. Smith, B. L., and Demetsky, M. J. (1997). "Traffic flow forecasting: Comparison of modeling approaches." J. Transp. Eng., 123(4), 261-266.
12. Tang, Y. F., and Lam, W. H. K. (2001). "Annual average daily traffic forecasts in Hong Kong." J. East. Asia Soc. Transp. Stud., 4(3), 145-158.
13. Tang, Z., de Almeida, C., and Fishwick, P. A. (1991). "Time series forecasting using neural networks vs. Box-Jenkins methodology." Simulation, 57(5), 303-310.
14. Transport Department. (1994-1999). The annual traffic census, Traffic and Transport Survey Division, Government of the Hong Kong SAR.