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Decision Trees for Pavement Maintenance and Rehabilitation
Multimillion dollars are spent annually for pavement maintenance and
rehabilitation. Selecting the right treatment at the right time for the right
location leads to efficient cost effective methods of managing pavements. The
new Federal Transportation bill requires state agencies to use a risk-based
approach for project selection and to implement modern pavement management
systems to determine cost effective strategies for managing the National Highway
System. Decision trees are also a
critical component of any pavement management system. The factors and thresholds used in the
decision tree can have a major impact on the outcome of proposed and planned
maintenance and rehabilitation projects.
Decision trees can also be used independently of the pavement management
system to determine pavement maintenance and rehabilitation strategies.
The objective of this synthesis study to document agency practices for
the following information:
- How was the decision tree for pavement
maintenance and rehabilitation developed?
- What are the different factors included in the
· Is the decision tree based on individual
distresses or composite scores?
· What are the thresholds used in the decision for
the different factors?
· Does the decision tree include a structural
· How often is the decision tree updated?
· How are the recommendations for treatments
provided by the decision tree validated?
· What are the similarities and differences
between decision trees used by agencies in the same climatic region?
Cost-effective funding allocation to pavement maintenance and rehabilitation to preserve the "State-of-Good Repair"
|Sponsoring Committee:||AFD10, Pavement Management Systems
|Research Period:||6 - 12 months|
|RNS Developer:||Magdy Mikhail (Texas Department of Transportation), Adrian Archilla (University of Hawaii), Carlos Chang (University of Texas at El Paso)|
|Index Terms:||Decision trees, Pavements, Pavement maintenance, Rehabilitation (Maintenance), |
Maintenance and Preservation
Planning and Forecasting
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