Decision Model - Group 4 - 2018/2019, Semester B, Quartile 3

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Introduction

In this section, we will describe our decision model. First, a description of what a decision model actually is will be given, to give a basic understanding of the concept. After that, we will explain what our decision model in fact does on a higher level, without all the details inside the decision model. After that, we will explain how the decision model is derived, and how our decision model works on a lower level.

What is a decision model?

A decision model

As described before, our decision model gives as output the best solution for anti-UAV systems based on the input of the user. This user can be, for example, an airport seeking to improve on its anti-UAV systems. Due to the enormous growing list of solutions for this, airports may find it difficult to decide for themselves. After our thorough analysis on solutions and types of airport, we have seen that some solutions fit certain airports better than others, and thus we decide to give a systemized model to consult users in this difficult choice.

How does our decision model work?

Our model is a so-called attributed-based decision model. This means that we deconstruct the concept of anti-UAV systems into a set of attributes. Each of these attributes will be quantified by a score between 1 and 10. Then, by asking our user certain question about each attribute, we can get the ideal score of the anti-UAV system that fits this user best.

Attributes

As described above, we will create a decision model that airports can use to decide on which type of anti-UAV system to deploy. For this decision model, we have deconstructed the needs of the airports into concrete attributes, which we have quantified by giving a score between 1 and 10. These attributes are based on the recommendation report. Here, we distinguished between three different types of airports and identified all the USE-stakeholders for each type. Furthermore, we did a risk analysis for each type of airport and a stakeholder analysis. Using this stakeholder analysis, we were able to set up a set of requirements, from which we have derived these core attributes. We will first summarise a list of these attributes to get a clear overview of what attributes are all taken into account when creating the decision model.

Airport specific attributes

These attributes are attributes that are intrinsic to an airport. They are attributes that cannot be changed based on preference. Although the airport cannot pick a preference here, they are important to keep into account when advising the best solution, since, e.g. the size of an airport can have a big influence on which type of solution fits the user's preferences best.

List of airport specific attributes:

  • Type of the airport (Commercial, Military, Recreational)
  • Size of the airport

Preference specific attributes

These attributes are not necessarily only dependent on the airport/user. For two airports with comparable sizes and type, one airport might decide to prioritise certain attributes over others. Since we want to centralize the user and give the user as much freedom of choice as possible, these preference specific attributes were added. Some preference attributes, like the safety of the solution for bystanders, may seem like an open door. However, our main goal of these attributes is to get a value to the priority of this attribute; some airports might prioritize safety moreover costs than other airports. To consult the airports, while giving these airports as much freedom in setting their own preferences, these open door attributes are included.

List of preference specific attributes:

  • Cost of the solution, this can be split up into two sub-attributes:
    • Initial costs (purchase)
    • Long term cost (maintenance)
  • Range of the solution
  • Deployment speed of the solution
  • Safety of the solution for bystanders
  • Emission of the solution (CO2)
  • Reliability of the solution
  • Hindrance to the immediate environment of the solution
  • Types of drones that the solution can be used for
  • Scalability of the solution in terms of a growing airport

Scoring the attributes

The next step is for the decision model to rank or score these attributes, so that the decision model can link the final outcome of the attributes to actual solutions. To score these solutions, multiple choice questions were used. As is usual in a decision model, the questions are dependent of what the user has answered to the previous questions. An example of scoring the attributes based on the questions is as follows:

Q: "How many people are living / working within 1km of the border of the airport?"

A:

[1]: 0-50 people, [2]: 50-100 people, [3]: 100-250 people, [4]: 250-500 people, [5]: 500-1000 people,
[6]: 1000-1500 people, [7]: 1500-2000 people, [8]: 2000-2500 people, [9]: 2500-3000 people, [10]: 3000+ people.

Based on this question, we can score the attribute "Hindrance to immediate environment of solution" with a score ranging from 1 (picking 0-50) to 10 (picking 3000+). All these questions are justified and all questions will be explained in greater detail (see section questions), so that each attribute can get a justified and well-calculated score. The main point of this example is to show how we are going to score attributes based on the questions that we ask.

Weighing the attributes

Now that our decision model has calculated the score of each attribute with respect to the preferences of the user, we must also appropriately weigh the attributes. In most cases, the emmision does not contribute equally to the choice in solution as the safety of the solution, to give an example. We will weigh these attributes as follows: We ask the user to rank the attributes based on what they find most important. Again, it is expected that some attributes will always receive a higher ranking with respect to importance (such as safety compared to emission), but as mentioned before, we want to give the user as much freedom in selecting the preferences to give a decision model that is as user-centered as possible. So, the user ranks all preference specific attributes from 1 to TODO, after which we can translate this to actual solutions.

Translating the attributes to advised solutions

After the questions of the decision model have been answered by the user, an actual solution can now be proposed. This will be done by scoring all current solutions that we currently have gathered from the state of the art literature, which we have grouped together under the section solutions. These scoring of the actual solutions will be done such that these scores match the questions of the decision model as close as possible. In relation to the example question, a solution that does not cause any hindrance at all to the surroundings will be given a score of 10, whereas a solution that causes an enormous amount of hindrance to the surroundings will receive a much lower score. We will give adequate and well-funded scores to all attributes of all solutions in this manner.

After having

Determining the outcome of the decision model

At the end of the model, we thus get an outcome for each attribute. We then assign weights to each attribute, and this is the final result that will uniquely determine the solution proposed by the decision model.

Questions

In this section, we consider questions regarding each of the attributes proposed earlier.

Cost of the solution

Initial costs (purchase)

Q: "How many euros would you be willing to spend on anti-drone mechanisms?"

A:

[1]: 0-100 euros, [2]: 100-1000 euros, [3]: 1000-5000 euros, [4]: 5000-10000 euros, [5]: 10000-100000 euros,
[6]: >100000 euros

Long term cost (maintenance)

Q: "How many euros would you be willing to spend on the anti-drone mechanisms after the initial purchase? (Think about future updates)"

A:

[1]: 0-100 euros, [2]: 100-1000 euros, [3]: 1000-5000 euros, [4]: 5000-10000 euros, [5]: 10000-100000 euros,
[6]: >100000 euros

Range of the solution

Q: "What diameter regarding the area consisting of the airport should the anti-drone mechanism cover?"

A:

[1]: <2 km, [2]: 2-5 km, [3]: 5-10 km, [4]: 10-15 km, [5]: 15-20 km,
[6]: >20 km

Deployment speed of the solution

Safety of the solution for bystanders

Emission of the solution (CO2)

Reliability of the solution

Hindrance to the immediate environment of the solution

Types of drones that the solution can be used for

Scalability of the solution in terms of a growing airport

.