Analysis tools in pavement management systems are critical to assist transportation agencies in developing the most adequate maintenance and rehabilitation program. A key aspect in the treatment selection process is to evaluate the effectiveness of maintenance and rehabilitation alternative treatments. Treatment effectiveness is related to the time of the application and should be measured in the short term and long term. Short-term treatment effectiveness measures include condition improvement and reduction of the deterioration rate, while long-term treatment effectiveness is related to its ability to extend the pavement remaining life. In this paper, a hybrid modeling approach is presented to integrate expert knowledge with pavement performance data for quantifying short-term and long-term treatment effectiveness. Optimal times to apply asphalt treatments were obtained as a result of the hybrid modeling approach. The Texas Department of Transportation (DOT) has successfully incorporated these results to enhance its pavement management information system, which is used as a tool to assist Texas DOT decision makers to formulate maintenance and rehabilitation programs.
Safety is a major worldwide concern due to the increasing number of fatalities of vulnerable road users (VRUs). VRUs are pedestrians, bicyclists, and motorcyclists, and their safety is a priority when making infrastructure management decisions. Traditionally, transportation agencies have adopted transportation asset management (TAM) practices based on performance measures to assess the physical condition of transport infrastructure. This paper describes a framework to incorporate VRU’s safety into the TAM decision-making process. The main objective of the VRU-TAM framework is to mitigate pedestrian fatalities by improving the decision-making process at the strategic and operational management level. The VRU-TAM framework is composed of four phases: assessment, prioritization, scenario analysis, and results. It includes a prioritization methodology using a safety-weighted effectiveness ratio (SWER) to consider pedestrian safety factors and costs in the decision-making process. In a broader perspective, pedestrian safety is affected by driver, demographic, pedestrian, infrastructure, and policy related factors. The decision-making criteria reflected in SWER considers the asset importance, location, pedestrian safety risk, costs, and remaining life in the budget allocation process, and adopts the dynamic bubble up (DBU) technique for budget prioritization at the network level. An example is presented for crosswalks to demonstrate the applicability of the methodology to evaluate different budget-driven scenarios for funding allocation. As a conclusion, it is demonstrated that the outcomes of the budget-driven scenarios following the method that incorporates safety criteria, with tangible metrics, offer a deeper understanding of the effects of budgetary constraints on backlog costs and the remaining life of infrastructure assets.
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