Off-Board Vehicle Transit Optimization for Arrival Time Accuracy
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Solution Overview
Problem
Current flight planning systems fail to effectively manage in-flight deviations such as weather, traffic, and payload changes, leading to disruptions in flight operations and arrival times, which can cause cascading effects on airline and ATC operations, ground handling, and passenger inconvenience.
Innovation Solution
A method and system that continuously monitor and optimize flight parameters like speed and route in real-time using an off-board system, integrating environmental conditions, traffic, and payload data to maintain the estimated time of arrival within a threshold, by re-planning speed profiles and routes, and evaluating the impact of optimization initiatives on overall mission parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If flight planning is done several hours before departure using forecast data, then operational efficiency is improved, but the system cannot respond to dynamic in-flight deviations such as weather changes, traffic conditions, and payload deviations
Solution Approach 1:
The system performs preliminary flight planning several hours before departure using forecast data to compute an operational flight plan. This preliminary action establishes an optimized baseline route and speed profile that anticipates expected conditions, allowing the system to prepare optimization strategies in advance while maintaining the ability to adapt to actual in-flight deviations through continuous monitoring and real-time adjustments.
2Reliability
If in-flight modifications are made to address dynamic factors, then safety and operational efficiency are improved, but the system complexity increases
Solution Approach 1:
The system continuously monitors actual flight conditions against the operational flight plan and uses feedback loops to detect deviations. When dynamic factors such as weather changes, traffic conditions, or payload deviations are detected, the system automatically adjusts the flight plan through controlled modifications to speed, route, or altitude. This feedback mechanism maintains safety by responding to actual conditions while managing complexity through structured, rule-based adjustment protocols.
3Loss of time
If the vehicle changes speed or route to maintain estimated time of arrival, then arrival time accuracy is improved, but the optimization process becomes more complex
Solution Approach 1:
The system dynamically adjusts flight parameters such as speed and route based on real-time conditions and deviation from the operational flight plan. When the estimated time of arrival deviates from the target arrival time, the system computes optimized speed profiles or route modifications to correct the timing. This dynamic adjustment capability maintains arrival time accuracy while managing optimization complexity through automated calculations that balance multiple constraints including safety, fuel efficiency, and operational requirements.
Data Source
AI summary
A method for optimizing a transit of a vehicle with an estimated time of arrival to a destination includes, during the transit of the vehicle, performing, by one or more processors located off-board the vehicle, operations including: receiving data impacting the estimated time of arrival of the vehicle to the destination; optimizing, based on the received data, a parameter for an operation of the vehicle to maintain the estimated time of arrival to the destination within a threshold time, wherein the optimizing the parameter includes changing one or more of a speed or a route of the vehicle; and sending the optimized parameter to the vehicle.