Vehicle Conflict Detection Using Segmented Cells
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Solution Overview
Problem
Existing systems face challenges in accurately and efficiently detecting conflicts between vehicles and restricted areas, particularly in complex airfield environments with multiple vehicles and non-trivial polygonal restricted areas, due to inexact position information and computational inefficiencies, which can lead to delayed alerts and increased collision risks.
Innovation Solution
A conflict detection system that uses transceiver circuitry and position determination circuitry to identify vehicle positions within segmented geographical cells, determining if they are within extended restricted areas by comparing positions to polygonal areas, and transmitting alerts when conflicts are detected, with the ability to extend restricted areas to account for measurement errors and vehicle sizes, thereby reducing false negatives and improving alert timing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system uses exact position information and precise polygonal area comparison for conflict detection, then the accuracy of conflict detection is improved, but the computational complexity and processing time increase significantly
Solution Approach 1:
The geographical area is divided into discrete cells, and the conflict detection process is segmented into multiple stages: first checking if the vehicle is in the same cell as the restricted area, then checking polygonal area intersection, and finally checking extended restricted area intersection. This segmentation reduces computational complexity by breaking down the problem into smaller, manageable steps.
Solution Approach 2:
The system performs preliminary actions by extending the restricted area footprint beforehand to create an extended restricted area that accounts for position errors and vehicle sizes. This preliminary extension simplifies subsequent conflict detection by eliminating the need for complex error calculations during real-time detection.
2Reliability
If the system extends the restricted area to account for measurement errors and vehicle sizes, then the reliability of conflict detection is improved, but the area requiring computation increases
Solution Approach 1:
The system performs preliminary actions by extending the restricted area footprint beforehand to create an extended restricted area that accounts for position errors and vehicle sizes. This preliminary extension simplifies subsequent conflict detection by eliminating the need for complex error calculations during real-time detection.
Solution Approach 2:
The system applies beforehand cushioning by creating an extended restricted area that acts as a buffer zone around the actual restricted area. This cushioning accounts for position measurement errors and vehicle dimensions in advance, ensuring that potential conflicts are detected before they occur, thereby improving reliability without requiring complex real-time calculations.
3Measurement precision
If the system uses a detailed polygonal area representation for restricted areas, then the precision of conflict detection is improved, but the processing speed decreases
Solution Approach 1:
The geographical area is divided into discrete cells, and the conflict detection process is segmented into multiple stages: first checking if the vehicle is in the same cell as the restricted area, then checking polygonal area intersection, and finally checking extended restricted area intersection. This segmentation reduces computational complexity by breaking down the problem into smaller, manageable steps.
Solution Approach 2:
The system performs preliminary actions by extending the restricted area footprint beforehand to create an extended restricted area that accounts for position errors and vehicle sizes. This preliminary extension simplifies subsequent conflict detection by eliminating the need for complex error calculations during real-time detection.
4Loss of time
If the system checks every vehicle position against the restricted area in real-time, then the timeliness of alerts is improved, but the use of computational resources increases
Solution Approach 1:
The geographical area is divided into discrete cells, and the conflict detection process is segmented into multiple stages: first checking if the vehicle is in the same cell as the restricted area, then checking polygonal area intersection, and finally checking extended restricted area intersection. This segmentation reduces computational complexity by breaking down the problem into smaller, manageable steps.
Solution Approach 2:
The system uses periodic action by implementing a multi-stage detection process that is triggered periodically or at specific events (vehicle position updates). The coarse filtering using cell identification is performed periodically, and only when this filter indicates a potential conflict does the system proceed to more computationally intensive checks.
Data Source
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AI summary
Generally discussed herein are methods and apparatuses that can reduce conflicts in an area including vehicles. An apparatus can include transceiver circuitry, and conflict detection circuitry to receive a position of a vehicle in a geographical area that is segmented into discrete cells, determine whether the position is situated in a cell of the cells that includes a polygonal area representing an extended restricted area within the cell, and the extended restricted area completely within the polygonal area, in response to a determination the position is situated within the polygonal area, determine whether the position is situated within the extended restricted area, and in response to a determination the position is situated within the extended restricted area, provide one or more signals to the transceiver circuitry to cause the transceiver circuitry to transmit an alert to the vehicle indicating that a conflict exists.