Project Lead | All |
Team Members | |
Objective | Generate an optimized velocity profile that minimizes energy usage within given constraints |
Due date | |
Key outcomes | |
Status | IN PROGRESS |
\uD83E\uDD14 Problem Statement
Research Optimization Legacy Code
Code Breakdown
Function: “load_course_map“
Parameters: The name of the course we’re trying to load in (course_name)
Returns: The map of elevations on said course (elev_profile).
The map of elevations has dimensions num_points x 2, with column 1 (Index 0) representing the y-coordinates and column 2 (Index 1) representing the x-coordinates.
Function: “generate_initial_profile“
Parameters: The maximum allowable time to cover a distance in seconds (time), the distance to be covered in meters (distance), the list of pitches map of elevations that the car must travel (e_profile), the minimum allowable velocity (min_velocity), and the list of indices where the car must stop (stop_profile)
Returns: A map of the same dimensions as the map of elevations with each element representing the average velocity required for the car to move at each point on the map of elevations (initial_profile).
Ex. initial_profile[2] = 10 means that according to the initial profile, the car should be moving 10 m/s at point 3 (Index 2) on the map of elevations.
This function basically generates the naive/initial solution that will be improved upon through the optimization function later in the program.
What does it accomplish?
Inputs/Outputs
Dependencies
Processing Outputs (how do we gain strategical advantage using the output)
🎯 Scope
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Nice to have: | |
Not in scope: |
\uD83D\uDDD3 Timeline
\uD83D\uDEA9 Milestones and deadlines
Milestone | Owner | Deadline | Status |
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