Final Competition - with Sensors

[tawheeler]

For the final competition, students will develop their own collision avoidance systems with partial observability. The collision avoidance systems will be filled out in provided .jl files, which will then be submitted. The objective is to minimize the number of collisions and the number of alerts (with some weighting between them).

The CAS implements reset() and tick(), the latter of which will receive observations rather than the true aircraft states (ie, range with Gaussian noise, bearing with Gaussian noise, and relative altitude quantized to a bin).

They cannot use any Julia libraries besides those used for the class (AA120Q.jl, Distributions, BayesNets, etc.)

TEACHERS provide:

• the API
• a set of pre-generated human traces from RLES-SISLES
• an example CAS that works
• code for running a CAS on the pre-generated human traces
• code for running a CAS on the full batch of human traces from which evaluation metrics are extracted
• Alpha-Beta Filters demo
• Outlier removal demo
• server runs 100,000 sims for each student using their CAS to compute a score

STUDENTS provide:

• their own implementation of a CAS by extending our provided CAS .jl file

[tawheeler]

Added SensorReading and PartiallyObservableCollisionAvoidanceSystem as of e8fd041

[tawheeler]

Added alpha beta filter to Solution.ipynb as of 95dce90