PILOT ADAPTABLE OPTIMAL PLANNING (POP)

THIS FEASIBILITY EFFORT WILL DEMONSTRATE NEURAL NETWORK-BASED (NN) AUTOMATED ROUTE PLANNING FOR AIRCRAGT, ADAPTABLE TO THE USER'S FLIGHT PREFERENCES AND MISSION NEEDS. THIS SYSTEM, TERMED PILOT ADAPTABLE OPTIMAL PLANNING (POP), WILL BE DESIGNED TO PERATE IN TWO MODES. IN THE FIRST MODE IT WILL PROVIDE THE MEANS FOR ROUTE PLANNING AND ESTIMATING THE SECCESS OF THE USER'S ROUTE PLAN BY FLYING AND TRAINING THE SIMULATED MISSIONS. THE USER WILL PRETRAIN MISSIONS FOR GENERAL REQUIREMENTS WITH FLIGHT PATTERNS CORRESPONDING TO THE USER'S INDIVIDUAL PREFERNCES. THERSE MISSIONS WILL BE COLLECTED IN MISSION SPECIFIC LIBRARIES. IN THE SECOND MODE, THE USER WILL SELECT AN APPROPRIATE MISION FORM THE LIBRARY AND OPTIMIZE IT TO THE DESIRED MISSION USING THE LATES INTELLIGNECE, MAPS, WEATHER, ETC. THIS WILL ACHIEVE TWO GOALS: (1) INTRODUCE PILAT FLIGHT PREFERENCES INTO REOUTE PLANNING AND (2) PROVIDE OPTIMIZATION OF ROUTE PLANS. THE PLAN CAN BE EVALUATED IN MONTE CARLO SIMULATION, WITH SCORING INDICATING THE PROBABILITY OF A SUCCESSFUL MISSION. IN OUR VISISON, THE PROPOSED POP SYSTEM WHOULD EVENTUALLY BE IPLEMENTED ON AN A MISSION PLANNING WORKSTATION LIKE MSS II AND MSS III WHERE IT MAY ENHANCE CURRENT ROUTE OPTIMATIZATION PROCESS.