Rehabilitation of aging roads has a significant impact on pavement performance and hence vehicle fuel consumption in transportation networks. Therefore, thorough analysis and evaluation of highway rehabilitation decisions and strategies can result in significant savings in fuel consumption in transportation networks. However, it is a challenging task to optimize highway rehabilitation decisions in order to minimize network fuel consumption and maximize net public benefits while satisfying several constraints such as limited funding and targets established for overall pavement performance. This paper presents a new model developed for optimizing and planning highway rehabilitation efforts that is designed to: (1) identify candidate rehabilitation treatment alternatives to deteriorating pavement; (2) evaluate and forecast the impact of implementing such treatments on pavement performance; (3) estimate total network fuel consumption as a result of selected rehabilitation decisions; (4) evaluate the cost of travel delay due to construction operations; (5) measure the impact of rehabilitation decision making on the expected savings in road user costs; and (6) optimize rehabilitation decisions to identify highway program(s) that simultaneously minimize network fuel consumption while maximizing net public benefits. The model is applied to a hypothetical example of an aging transportation network example in South Florida and was capable of generating optimal tradeoffs between public benefits and fuel consumption. This model should prove useful to state highway agencies in identifying and implementing cost-effective and energy-efficient highway rehabilitation programs.


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    Title :

    Optimizing Highway Rehabilitation Decisions to Minimize Fuel Consumption in Transportation Networks


    Contributors:

    Conference:

    Construction Research Congress 2016 ; 2016 ; San Juan, Puerto Rico


    Published in:

    Publication date :

    2016-05-24




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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