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. For each loop we want to determine a cost to benefit ratio based on the loop properties such as

Distance

Want to know 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:

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Project Summary

The Loops Optimization sub-project is focused on building models to analyze and forecast loops effectiveness and efficiency to our distance-maximizing performance. The loops team is building models for before and during the race.

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).