Maintenance Decision Support System
Controlling snow and ice buildup on roadways during winter weather events presents several challenges for winter maintenance personnel. Among these challenges is the need to make effective winter maintenance decisions (treatment types, timing, rates, and locations), as these decisions have a considerable impact on roadway safety and efficiency. Additionally, poor decisions can have adverse economic and environmental consequences. In an effort to mitigate the challenges associated with winter maintenance decisions, the Federal Highway Administration (FHWA) Office of Transportation Operations (HOTO) initiated a program in 2001 aimed at developing a winter road Maintenance Decision Support System (MDSS).
The MDSS project goal is to develop a prototype capability that:
- Capitalizes on existing road and weather data sources
- Augments data sources where they are weak or where improved accuracy could significantly improve the decision–making task
- Fuses data to make an open, integrated and understandable presentation of current environmental and road conditions
- Processes data to generate diagnostic and prognostic maps of road conditions along road corridors, with emphasis on the 1–to 48–hour horizon (historical information from the previous 48 hours will also be available)
- Provides a display capability on the state of the atmosphere and roadway
- Provides a decision support tool, which provides recommendations on road maintenance courses of action
- Provides all of the above on a single platform, with simple and intuitive operating requirements, and does so in a readily comprehensible display of results and recommended courses of action, together with anticipated consequences of action or inaction
Release–6 is now available. Changes since Release–5 (Nov 2007) include new data sets that help to provide additional tactical information on weather events. Data such as Automated Vehicle Location (AVL) information, truck camera images, and webcam images from fixed locations can now be viewed on the display. The observation processing subsystem has been enhanced to allow easier addition of forecast sites by using weather forecast elements as surrogates for missing Environmental Sensor Station (ESS) observation data. This allows new (and intermittently observing) sites to work more seamlessly within the requirements of the road temperature model called Model of the Environment and Temperature of Roads (METRo). An event playback capability has been added to view previous weather forecasts and treatment recommendations. This capability requires that previous data be maintained on the MDSS server for an extended period of time, dependent on disk resources. Initial work was performed to transition the source of ESS data from MADIS to the new Clarus system (http://www.clarus-system.com/). The components of this work are included, but because of the lack of ESS data available from the Clarus system covering the demonstration area (Colorado), these components were not completely interfaced to the MDSS system.
Although NCAR/RAL has been the lead laboratory in terms of MDSS development, several national laboratories have contributed considerably during the life cycle of the system, including the Cold Regions Research and Engineering Laboratory (CRREL), Massachusetts Institute of Technology–Lincoln Laboratory (MIT/LL), and the National Oceanic and Atmospheric Administration's–Global Systems Division (NOAA/GSD).