Document Type



Doctor of Philosophy (PhD)


Civil Engineering

First Advisor's Name

Wallied Orabi

First Advisor's Committee Title

Committee Co-Chair

Second Advisor's Name

Berrin Tansel

Second Advisor's Committee Title

Committee Co-Chair

Third Advisor's Name

Irtishad U. Ahmad

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

Arindam Gan Chowdhury

Fourth Advisor's Committee Title

Committee Member

Fifth Advisor's Name

Shonali Laha

Fifth Advisor's Committee Title

Committee Member


Highway Rehabilitation, Highway Programming, Transportation Networks, Sustainability, Energy Consumption, CO2 Emissions, Optimization

Date of Defense



Transportation agencies face a challenging task to repair damaged roads in an aging transportation network with limited funding. In addition, the funding gap is forecasted to continue widening, which has direct impacts on the performance of surface transportation networks and the nation’s economy in the long run. Recently, transportation agencies were required by a newly enacted law to include national performance-based goals, such as environmental sustainability, in their programming and planning efforts for highway repair and rehabilitation. Therefore, the current practice in the area of highway rehabilitation planning is inadequate to handle this task and new practices are needed to improve the performance of transportation networks while maintain the national goal of maximizing environmental sustainability. Accordingly, this dissertation presents an innovative environmental-based decision-support model for planning highway construction programs. The model is developed in three main parts that are designed to: (1) model total vehicle fuel consumption and public benefits/costs of traveling on transportation networks; (2) evaluate the economic and environmental impacts of highway rehabilitation efforts; and (3) develop a multi-objective optimization model to identify and evaluate highway rehabilitation program(s) that are capable of simultaneously minimizing environmental impact and maximizing public benefits of rehabilitation decisions.

First, mathematical models were developed to facilitate estimating the total vehicle fuel consumption and public benefits/cost for road users at the network-level. These models are deigned to estimate vehicle fuel consumption rate, tire depreciation cost, and vehicle repair and maintenance cost rate, in terms of major vehicle–road interaction factors, such as vehicle type, speed, and pavement conditions. The developed and statistically validated models are then used to estimate total vehicle fuel consumption and public benefits/costs at the network-level.

Second, a new model was developed for evaluating the impact of decision making in highway rehabilitation efforts on greenhouse gas emissions and public travel costs. The model has the capabilities of: (1) identifying candidate rehabilitation treatment alternatives for damaged or aging pavement; (2) evaluating the impact of these treatments on pavement performance; (3) estimating network fuel consumption due to highway rehabilitation decisions; (4) estimating additional public costs as a result of travel-delay during road construction operations; and (5) evaluating the impact of rehabilitation efforts on public benefits expressed as expected savings in road user costs.

Third, a multi-objective optimization model was developed to search for and identify highway rehabilitation programs that are capable of minimizing environmental impact in terms of CO2 emissions while maximizing public benefits under budget constraints. This newly developed model enables planners and decision makers to design and implement highway rehabilitation programs that are cost-effective and environmentally-conscious.





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