Pooled Fund Study TPF-5(347), which now includes the states of Connecticut, Illinois, Indiana, Maryland, Minnesota, Nebraska, North Dakota, South Dakota, and Wisconsin began in October 2002 to develop a Maintenance Decision Support System (MDSS) that satisfies the needs of these states and meets national expectations for a deployed MDSS. Former states in the MDSS PFS have included California, Colorado, Idaho, Iowa, Kansas, Kentucky, Michigan, Pennsylvania, New York, New Hampshire, Virginia, and Wyoming. The project was initiallyproposed as a multi-year project divided into several distinct phases. The first phase consisted of extensive customer surveys, the construction of a design framework, and a review of existing work conducted by the National Laboratories as part of an MDSS Functional Prototype development. The second phase comprised development and implementation of a limited deployment testing and development of the initial version of the MDSS PFS operational prototype.

After the initial project phases, the primary work involved deployment field operational testing of the initial and refined prototype releases during the 2004-05 and 2005-06 winter seasons. Operational refinement continued during the field deployment transition phase, beginning in the 2006-07 winter season and continuing through the 2018 - 2019 winter season. As new agencies have joined the Pooled Fund Study, they have progressed from operational testing to Deployment Field Trials and to fully operational deployment outside of the pooled fund study.

The pooled fund study has continued to advance the science and technology of winter maintenance decision support in recent years through assessment and improvement of maintenance recommendations, incorporation of innovative deicing materials, refinement of the pavement condition prediction model, and significant improvement of computational analytics. The MDSS user interface has advanced from a client application to a fully web-based application, a mobile app, and an onboard app for snowplows. The MDSS employs onboard sensors and hydraulic controllers to dynamically monitor road conditions and applied maintenance treatments, both of which affect future maintenance treatment recommendations. The MDSS is poised for additional refinement and enhancements through another pooled fund effort.

The objectives of the Maintenance Decision Support System are to:

     Assess current road and weather conditions using observations and reasonable inferences based upon observations and physical laws.

     Provide time- and location-specific weather forecasts along transportation routes.

     Predict how road conditions would change due to the combined effects of the forecast weather and the application of several candidate road maintenance treatments.

     Notify state agencies of approaching adverse conditions and suggest optimal maintenance treatments that can be achieved with resources available to the transportation agencies.

     Evaluate the reliability of predictions and the effectiveness of applied maintenance treatments for specific road and weather conditions so that the decision support logic can be improved.

Continuing the efforts of the previous phases of work, the member agencies voted on the future direction and tasks of the MDSS PFS. Some of these tasks represent continuation of previous phases of work and others are new endeavors for the project. The primary research areas selected by members of the MDSS project panel include:

•          Investigate methods to improve the MDSS model for better support of frost, freezing rain and other weather conditions

•          Assess recommendations based on user feedback in real-time with post-recommendation analysis to improve MDSS modeling

•          Analyze the use of Level of Service in DOT operations and understand how this functionality can be improved within MDSS

•          Focus on Liquids as a priority treatment recommendation and develop processes that facilitate specialty liquids within MDSS

•          Conduct a discovery process on Performance Measurement methods that would be applicable for MDSS with the goal of implementing these methods to demonstrate MDSS value

•          Improve the Route Configuration Process by implementing automated functionality, clear guidance for users, and preparing for the future of MDSS

These research tasks will be conducted in addition to the operational design and development activities associated with the MDSS Pavement Model,  WebMDSS , Mobile App, and In-Vehicle App.