Project Summary
The loops Loops Optimization sub-team project is focused on building models to analyze whether to take loops during the raceand forecast loops effectiveness and efficiency to our distance-maximizing performance. The loops team is building models for before and during the race.
Benefit-Cost Score
Project Summary
This model scores loops prior to the race beginning based on various factors.
Goal
The goal of this model is to be able to calculate the “efficiency score” or reward for each loop to determine which one to take.
Inputs
For each loop we want to determine a cost to benefit ratio based on the loop properties, which include:
Distance
How much the additional distance will increase our score.
Stop/Start Moments
Accelerating/ Decelerating from/to stop will have an effect on energy consumption so we need to look at how we can minimize this. This isn’t an additional variable it directly impacts our power expenditure amount. Some extra reasons for stopping could be; Railroad tracks, weather, pedestrian crosses, or other stop causes not specified.
Speed Limits
The speed limit of the current road will also have an effect on the power that we consume. We need to look at how much power will be consumed by the current speed limit but also the km/h increase to a different speed limit.
Turns and their Steepness (90 degree or 120 degree)
Turns will also have an effect on our score. Not only using more power they also give us more points:
3 Levels
1-easy
2-medium
3-hard
Multiply number of turns by difficulty of each
Example:
2 easy turns
3 medium
1 hard
Total Turn Score: 2(1)+3(2)+ 1(3)= 11
Estimated Completion Time
We need to look at being able to estimate the total minutes for each loop. This can be calculated simply by using speed / distance, or as we take in more variables can get more accurate. The current status (20 miles behind projected distance or 15 miles ahead) will act as weight for this variable. We then want to be able to calculate the average loop completion time:
If loop time > average loop, difference will act as negative and be affected by current status
If loop time < average loop, difference will act as positive and be affected by current status
Output
...
Goals
Determine the types of data needed to make decisions about which loops to take or not to take
Build a model that determines which loop to take prior to the race starting
Build a model that determines which loop to take based on real-time race conditions as well as how to take the loop (speed, other factors).