The focus of this research is Virginia’s Secondary Highway Construction System funding allocations and its impact on statewide deficient lane miles reduction. The research question guiding this study is: “Which of the four allocation models -- the current Secondary Highway System allocation model or one of three alternatives of this model based on Brian D. Taylor’s geographic equity categories (outcome, opportunity, and market) best maximizes statewide deficient lane miles reductions?” Taylor defines each of these geographic equity categories (independent variables for this study) for all levels of government. While Taylor’s research focus has been on equity as it relates to transit and congestion pricing, this study applied his construct to highways. As a result of scanning subjects related to transportation, the need for this study became apparent. Since the 1980’s, Virginia’s highway allocation formula has not changed (Virginia Department of Transportation, 2005). The Virginia General Assembly has sponsored follow-up studies through a series of resolutions over the years (Auditor of Pubic Accounts, 2004). To date, none of the legislatively sponsored research findings have prompted an update of Virginia’s highway allocation formula (Virginia Transportation Research Council, 2008). There is a significant academic and professional literature on federal transportation politics and specific transportation engineering issues. However, there is very limited research on the development of state level highway transportation funding methodologies. This study used the quantitative research approach, which is concerned with determining the relationship between one factor (an independent variable) and another (a dependent or outcome variable) in a population (Walker, 2005, Newman, 1998, and Geddes, 1990). Therefore, this study employed the quantitative research approach to study cause and effect (Mulhall, 2004, Loughborough, 1995, and Collier 1995) relationships of Virginia’s Secondary construction allocations to individual counties and statewide deficient lane miles reductions overall. The .20 portion of the formula for area was examined because this data rarely changes due to locality annexations. Conversely, the .80 portion of the formula was excluded from the analysis because of the demographic variability due to population shifts. As such, the Federal Highway Administration and states update population statistics from the decennial census with the apportionment of funds for formula based programs such as Virginia’s Secondary Highway Construction program (Federal Register, 2002). This researcher concluded that of the four geographic allocation models, the geographic opportunity equity maximized an additional 4.15 statewide deficient lane miles reductions over the baseline model. This study recommends using the geographic opportunity equity model when allocating Virginia’s Secondary Highway Construction funds to maximize the statewide deficient lane miles reductions above the baseline model, the geographic market equity model and the geographic outcome equity model.