Impact of Escalating Construction Costs on Long-Term Pavement Performance Loss

Escalating construction costs caused by increasing crude oil prices have a serious impact on long-term pavement performance. There is an urgent need for transportation agencies to quantify the impact of the long-term loss of pavement performance (LOPP) and the additional pavement preservation need. This paper proposes a mathematical model that can be used to quantify LOPP. Historical data from the Georgia Department of Transportation (GDOT) from fiscal years (FYs) 1999 to 2007, including pavement survey data and resurfacing expenditures, were used to develop Markovian transition probability matrices. The average annual escalation rate (AAER), 18.1%, was obtained by analyzing the historical resurfacing costs. The impacts of different AAERs (15%, 20%, 30%, and 40%) were analyzed. At GDOT's current funding level, the results show that the composite rating of the non-Interstate pavement network with a 40% AAER would drop to 70 almost 2 years earlier than the one with a 15% AAER. If the AAER is increased from 15% to 30%, the pavement preservation cost needed to meet the expected pavement condition triples from $1.1 billion to $3.4 billion. The LOPP that would occur if there were a sudden increase in construction costs (50%, 100%, and 150%) within a single year was also analyzed. The results showed a 7.8% LOPP for a 100% sudden increase in construction costs in FY 2009. With the impact quantified, it is hoped that transportation agencies can communicate with their state legislatures and stakeholders more transparently about their actual funding needs because of escalating construction costs. Finally, recommendations on improving the accuracy of forecasting are also discussed.

[1]  Kamal Golabi,et al.  A Statewide Pavement Management System , 1982 .

[2]  Ying Wang,et al.  Genetic Algorithm‐Simulation Methodology for Pavement Maintenance Scheduling , 2004 .

[3]  António Pais Antunes,et al.  PROBABILISTIC SEGMENT-LINKED PAVEMENT MANAGEMENT OPTIMIZATION MODEL , 2002 .

[4]  P D Thompson.  MAKING OPTIMIZATION PRACTICAL IN PAVEMENT MANAGEMENT SYSTEMS: LESSONS FROM LEADING-EDGE PROJECTS , 1994 .

[5]  Khaled A. Abaza.  Expected Performance of Pavement Repair Works in a Global Network Optimization Model , 2007 .

[6]  Khaled A. Abaza.  Iterative Linear Approach for Nonlinear Nonhomogenous Stochastic Pavement Management Models , 2006 .

[7]  Samuel H Carpenter,et al.  APPLICATION OF MARKOV PROCESS TO PAVEMENT MANAGEMENT SYSTEMS AT NETWORK LEVEL , 1994 .

[8]  Weng Tat Chan,et al.  GENETIC-ALGORITHM PROGRAMMING OF ROAD MAINTENANCE AND REHABILITATION , 1996 .

[9]  Singiresu S. Rao.  Engineering Optimization : Theory and Practice , 2010 .

[10]  T H Maze,et al.  NETWORK PAVEMENT MANAGEMENT SYSTEM USING DYNAMIC PROGRAMMING: APPLICATION TO IOWA STATE INTERSTATE NETWORK , 1994 .

[11]  Kelvin C. P. Wang,et al.  Probabilistic Behavior of Pavements , 1994 .

[12]  Suleiman Ashur,et al.  Integrated Pavement Management System with a Markovian Prediction Model , 2004 .

[13]  Samuel H Carpenter,et al.  PAVEMENT PERFORMANCE PREDICTION MODEL USING THE MARKOV PROCESS , 1987 .

[14]  Ralph Haas,et al.  Integer Programming of Maintenance and Rehabilitation Treatments for Pavement Networks , 1998 .

[15]  Y. Ouyang,et al.  Optimal scheduling of rehabilitation activities for multiple pavement facilities: exact and approximate solutions , 2004 .

[16]  Michel Gendreau,et al.  Airport pavement management systems: an appraisal of existing methodologies , 1998 .

[17]  C L Monismith,et al.  DYNAMIC DECISION MODEL FOR PAVEMENT MANAGEMENT USING MECHANISTIC PAVEMENT PERFORMANCE SUBMODEL , 1993 .

[18]  Ralph Haas,et al.  RELIABILITY-BASED PROCESSING OF MARKOV CHAINS FOR MODELING PAVEMENT NETWORK DETERIORATION , 1996 .

[19]  Yanfeng Ouyang,et al.  Pavement Resurfacing Planning for Highway Networks: Parametric Policy Iteration Approach , 2007 .

[20]  Weng Tat Chan,et al.  Multiobjective Optimization for Pavement Maintenance Programming , 2000 .