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This webinar was co-sponsored by ASCE's Transportation and Development Institute (T&DI) and ASCE Continuing Education
Instructor: David K. Hein, P.Eng.
Course Length: 1 Hour
Purpose and Background
Roadway owners across North America have collectively constructed trillions of dollars of roadway infrastructure including pavements, bridges, safety appurtenances, drainage structures, etc. Our focus over the past 30 years or so has changed from the construction of new transportation infrastructure to maintenance and rehabilitation of existing facilities. In order to assist in “managing” the infrastructure, agencies have developed processes and procedures such as pavement management systems.
A pavement management system uses asset condition data to monitor the rate of deterioration of their pavement infrastructure. Deterioration models are typically developed for pavement surface distress and some agencies incorporate pavement smoothness, rut depth, surface friction and an indication of structural capacity in the overall condition index which typically ranges from 0 (failed) to 100 (excellent).
The process for the development of deterioration models typically includes the segregation of highway pavement sections by one or more of the following elements:
- Highway classification
- Pavement surface type (rigid, flexible, chip seal, etc.)
- New construction or rehabilitation
- Pavement base/subbase type (unbound granular, stabilized, etc.)
- Age since construction or last rehabilitation
- Subgrade type
- Climate (wet freeze, wet no freeze, dry freeze, dry no freeze, etc.)
- Traffic level
- Other relevant local factors that may impact pavement performance
One of the key factors of the items outlined above is age since construction or last rehabilitation. Grouped sections are then analyzed by age and condition to develop performance prediction models. These models provide an indication of asset performance and establish target levels of service for maintenance and rehabilitation activity and timing as well as funding needs. Given the variability of performance of pavement assets, it can be very difficult to develop models that provide accurate and repeatable results that can easily be understood by all stakeholders.
Primary Discussion Topics
This webinar provides an overview of the importance and use of performance models for pavement management, outline deterministic (regression) and probabilistic (Markov probability, survival analysis and Bayesian techniques) statistical methods and tools for the evaluation of pavement condition data, provide examples of common performance model development. The quality of input data will be discussed, treatment of outliers, methods for calculating confidence bands such as bootstrapping, etc. will be provided.
Learning Outcomes
Upon completion of this course, you will be able to:
- Identify the key performance modelling input data
- Recognize potential sources of error
- Determine available statistical tools to develop performance models
- Describe methods used to update and improve performance models for pavements
Webinar Benefits
- Learn about performance modelling tools
- Quantify the quality and reliability of good data
- Understand what data needs to be collected and why
- Understand the elements that may impact the performance models
Assessment of Learning Outcomes
Students' achievement of the learning outcomes will be assessed via a short post-assessment (true-false, multiple choice and fill in the blank questions).
Intended Audience
- Civil engineers, statisticians and data managers responsible for the collection, processing and use of pavement performance data
- Agencies and other owners of highway, municipal and private sector pavement infrastructure
- Operations personnel responsible for the maintenance and rehabilitation of pavements
Webinar Outline
- Overview of the importance and use of performance models
- What data to collect and why
- Data quality and reliability
- Types of performance models
- Examples of performance model development
- Assessment methods to improve performance models
How to Earn your CEUs/PDHs and Receive Your Certificate of Completion
To receive your certificate of completion, you will need to complete a short on-line post-test and receive a passing score of 70% or higher within 1 year of purchasing the course.
How do I convert CEUs to PDHs?
1.0 CEU = 10 PDHs [Example: 0.1 CEU = 1 PDH]