An Integrated Feasibility Management, LCCA, and ANN Framework for Sustainable Highway Construction Zone Maintenance

The construction zones on the highways require a balanced situation that is inclusive of feasibility, safety, environmental accountability and long term efficiency in the maintenance. The current research creates a united approach of feasibility management within highway construction areas through the synthesis of case-based evaluation, life cycle cost analysis and the use of Artificial Neural Networks to predict future maintenance assistance. The research assesses the existing feasibility management as well as evaluates the environmental and safety implication and studies the maintenance strategies that are meant to enhance long-term infrastructure sustainability. The analytical stage involves two highway contexts which include the section of the Aurangabad Highway to Kolwadi Road and the Mumbai-Pune Expressway section. The rigorous and flexible pavements are evaluated comparatively over 30 years with a discount rate of 12 percent and 5 percent inflation rate. The results demonstrate that rigid pavement is more expensive in its initial construction but becomes cost-effective in the long run due to the reduced maintenance needs, and the break-even point is reached in 2029. In one instance, rigid pavement will be 10.39% less expensive than in another, 2048. ANN component will be implemented in MATLAB as a backpropagation feed-forward network with the TRAINLM, LEARNGDM, Mean Squared Error, and 10 neurons in the first layer to help in the future prediction of maintenance cost. The research comes up with a conclusion that a comprehensive approach to sustainable highway maintenance planning includes feasibility assessment, lifecycle economics, safety considerations, and predictive analytics.