A Network-Level Decision Making Tool for Pavement Maintenance and User Safety

PI: Erdem Coleri (OSU), erdem.coleri@oregonstate.edu
Dates: 12/16/2015-12/15/2016
Status: Completed
UTC Project Information
Final Technical Report

Data from NCHRP 720 report (Chatti and Zaabar, 2012) show that reducing the road roughness by maintenance and rehabilitation can create $0.4 to $0.8 reduction in user costs (mostly related to vehicle maintenance and fuel consumption) for one truck for one lane mile. This data alone suggests that hundreds of millions of dollars can be saved annually by developing more effective pavement management strategies for the entire Pacific Northwest road network. The network-level decision making software proposed here will help state Department of Transportation (DOT) engineers select the most efficient maintenance and rehabilitation strategies to minimize cost and maximize user and agency benefits. Proposed procedure will also consider road user safety by evaluating the effects of pavement surface texture, distresses, and international roughness index (IRI), a standardized pavement measurement indicating the overall smoothness of a roadway, on skid resistance and accident rates. Developed tool can also be used to evaluate and emphasize the effectiveness of sustainable pavement strategies such as high recycled asphalt pavement (RAP) mixtures and thin overlays. In the future, developed software can be modified to consider reduction in greenhouse gas (GHG) emissions as a benefit to perform pavement life cycle assessment (LCA).

This research would have three major objectives: i) develop a network-level decision making tool to more efficiently allocate state DOT resources for pavement maintenance and rehabilitation by considering road user safety and user-agency costs from construction and use phase stages; ii) develop distributions of optimum IRI trigger values, the optimum roughness level at which pavement needs to be considered for maintenance or rehabilitation, for different traffic levels and climate regions in the Pacific Northwest; iii) evaluate the network-level impact of pavement roughness and distress on vehicle operating costs and user safety.