## 1 Introduction  
There exist various measurable outcomes when implementing a change in traffic control strategy such as the increase in average travel speed, reduction in total traffic delay, and lowering of greenhouse gas emissions. One must assess the efficacy of the change through the collection of quantitative and qualitative data. These results assist decision-makers in deciding whether implementing the strategy is a viable solution to a problem, or if the benefits of doing so are outweighed by the cost. However, issues arise when decisions are so broad as to involve multiple bodies and agencies in approving them. These disparate parties may agree on a specific policy when there are no disadvantages but may conflict with each other when one party benefits at the expense of another. Citing some examples, many traffic agencies would prefer to extend the width of roads to increase the capacity and flow rate of traffic, but this process may be too expensive for the governmental agency in charge of funding it. It could also be too taxing on the environment with removed greenery and increased pollutants, which may cause agencies like the Environmental Protection Agency (EPA) to deny the project. The time and manpower necessary to make the extension could choke the present traffic flow to unacceptable levels, causing district traffic agencies to refuse to collaborate. As such, it is important to test each suggested alternative through multiple perspectives and criteria. Although this may still lead to some involved parties suffering additional costs, it does allow those parties to compromise on a decision and mitigate the negative aspects for the slighted parties. The original research reported here was performed as part of the doctoral thesis for co-author [PERSON] [1], who sought to improve the efficiency of freight truck movement. The thesis consisted of two main sections: the introduction, modeling, and testing of an autonomous traffic management strategy; and another section where it was assessed qualitatively by using a Multi-Criteria Decision Model (MCDM). The traffic strategy implemented featured truck platooning, wherein trucks were organized into convoys of indeterminate length, formed within an exclusive truck lane. Unfortunately, little research has been performed on this type of control, as it involves providing more freedom to truck movement when most strategies involve limiting them, whether in speed or transitionary movement. While the strategy can be modeled, and quantitative data gathered, the efficacy of the strategy will face resistance as most departments in charge of transportation are predisposed to limiting freight truck movement. As such, results that simply state the strategy will increase productivity would face criticism from parties concerned over the effects on traffic safety and mobility. However, if the MCDM successfully accounts for all these potential perspectives and proves the strategy will be effective enough in each area to placate those concerns, the results of the model will be seen with higher authenticity. For this paper, the authors will focus on the creation and implementation of the MCDM, as well as how the results can be used in future decisions. Starting with the literature research performed to determine the best model to use (Section 2), this report will then detail the methodology used in the creation of the model (Section 3), followed by the results of the implementation (Section 4), before considering potential weaknesses and criticisms (Section 5) and forming the ultimate conclusion on the efficacy of the MCDM (Section 6). The MCDM chosen was the Analytical Hierarchy Process (AHP) model, wherein each perspective and its criteria will be set into a tiered structure so that each criterion can be weighted with respect to the others in terms of overall value and desirability. This model was introduced by [PERSON] [2] and has seen use in several experiments and research, such as [PERSON] et al.