Estimation of infrastructure performance models using state-space specifications of time series models

Transportation Research Part C: Emerging Technologies

Volumn 15, Issue 1, 2007, Pages 17-32

  Chu, Chih Yuan ^a   Durango Cohen, Pablo L ^a  

^a Northwestern University   (United States)

Author keywords

Advanced inspection technologies; Infrastructure performance modeling; Maintenance optimization; Missing data; State space models; Time series analysis

Indexed keywords

DETERIORATION; INSPECTION; MAINTENANCE; MARKOV PROCESSES; MATHEMATICAL MODELS; OPTIMIZATION; TIME SERIES ANALYSIS;

AUTOREGRESSIVE MOVING AVERAGE MODELS; INFRASTRUCTURE PERFORMANCE MODEL; TRANSPORTATION INFRASTRUCTURE FACILITIES;

STRUCTURAL ANALYSIS;

MARKOV CHAIN; PAVEMENT; PERFORMANCE ASSESSMENT; TIME SERIES ANALYSIS; TRANSPORTATION INFRASTRUCTURE;

EID: 33947201092     PISSN: 0968090X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trc.2006.11.004     Document Type: Article

References (18)

1. AASHTO. AASHTO Guide for Design of Pavement Structures 1993 (1993), American Association of State Highway and Transportation Officials, Washington, DC
2. Ben-Akiva M., and Gopinath D. Modeling infrastructure performance and user costs. Journal of Infrastructure Systems 1 1 (1995) 33-43
3. Ben-Akiva M., and Ramaswamy R. An approach for predicting latent infrastructure facility deterioration. Transportation Science 27 2 (1993) 174-193
4. Chu, C.Y., Durango-Cohen, P.L., 2005. Estimation of latent infrastructure performance models using time series analysis. ASCE Journal of Transportation Engineering (under review).
5. Chu, C., Durango-Cohen, P.L., 2006. Estimation of dynamic performance models for transportation infrastructure using panel data: An application of multivariate time series analysis. Transportation Research Part B (under review).
6. Durango-Cohen, P.L., 2006. A time series analysis framework for transportation infrastructure management. Transportation Research Part B, in press, doi:10.1016/j.trb.2006.08.002.
7. Durbin J., and Koopman S.J. Time Series Analysis by State Space Methods (2001), Oxford University Press, New York, NY
8. Golabi K., and Pereira P. Innovative pavement management and planning system for road network of Portugal. Journal of Infrastructure Systems 9 2 (2003) 75-80
9. Gramling W.L. Current Practices in Determining Pavement Condition (1994), National Academy Press, Washington, DC
10. Harvey A.C. Forecasting, Structural Time Series Models and the Kalman Filter (1990), Cambridge University Press, New York, NY
11. Humplick F. Highway pavement distress evaluation: modeling measurement error. Transportation Research Part B 26B 2 (1992) 135-154
12. Madanat S., and Ben-Akiva M. Optimal inspection and repair policies for infrastructure facilities. Transportation Science 28 1 (1994) 55-61
13. Madanat S.M., Karlaftis M.G., and McCarthy P.S. Probabilistic infrastructure deterioration models with panel data. Journal of Infrastructure Systems 3 1 (1997) 4-9
14. Mishalani R.G., and Madanat S.M. Computation of infrastructure transition probabilities using stochastic duration models. Journal of Infrastructure Systems 8 4 (2002) 139-148
15. Morf M., and Kailath T. Square-root algorithms for least-squares estimation. IEEE Transactions on Automatic Control 20 4 (1975) 487-497
16. Palmquist, D., Worel, B., Zerfas, W., 2002. 2002 Mn/ROAD Hot-mix Asphalt Mainline Test Cell Condition Report. Office of Materials and Road Research, MnDOT, MN.
17. Paterson W.D.O. Road Deterioration and Maintenance Effects: Models for Planning and Management (1987), The Johns Hopkins University Press, Baltimore, MD
18. Zerfas, W.J., 2003. 2002 Superpave Report. Office of Materials and Road Research, MnDOT, MN.