This application was developed to expand a low-cost asset inventory program called Geographic Roadway Inventory Tool (GRIT) to include roadway forecasting based on the American Association of State Highway and Transportation Officials (AASHTO) 93 model with inventory; pavement condition; and traffic forecasting data. Existing input data from GRIT such as pavement thickness; roadway structural information; and construction planning information will be spatially combined with current MnDOT Pathway pavement condition and traffic data to automatically forecast the future condition and age of roadways using the AASHTO 93 model. This forecasting model will allow roadway managers to use this information with comprehensive geographic information system (GIS) web maps to prioritize roadways in their construction schedules or multi-year plans.
Horizontal curves account for more than 25% of highway fatal crashes and have a crash rate that is three times that of other highway segments. Transportation agencies employ dynamic warning systems that utilize roadside speed detection and warning equipment to provide drivers with a warning when they enter a curve at a speed that might be too high for safe travel. The goal of this project is to develop a system to expand the safety improvement potential of a dynamic curve speed warning system that can be implemented systemwide to all reduced speed curves without infrastructure investment. The system emulates a connected vehicle environment by utilizing a smartphone application to deliver dynamic; speed-based; directional warnings at locations in an online database. Transportation agencies are able to enter and manage the warning locations within their jurisdictions in the online warning database through a web-based tool; and it is envisioned that the warning data would be made available to navigation systems and vehicle manufacturers via the cloud.
