Centralized Vehicle Guidance for Multi-Object Collision Avoidance
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Solution Overview
Problem
Current collision avoidance techniques are inadequate for detecting and preventing collisions between vehicles or objects with near-parallel trajectories and velocities, particularly in scenarios involving multiple vehicles or objects, and fail to provide effective real-time guidance in 3-dimensional domains, such as space vehicle operations.
Innovation Solution
A centralized coordinated vehicle guidance system that collects and analyzes data from multiple vehicles and objects to predict potential collisions, determining trajectory adjustments to avoid collisions by using a Constraint Wrap technique, which optimizes fuel efficiency and minimizes reaction energy demands, even for vehicles traveling in the same direction or opposite directions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current collision avoidance techniques are used, then single vehicle-object immediate avoidance is addressed, but multiple vehicle collision prediction and near-parallel trajectory avoidance are not effective
Solution Approach 1:
The system segments the collision avoidance problem into multiple hierarchical levels: individual vehicle-object pair analysis and multi-vehicle system-wide analysis. This allows the system to handle both simple single-pair avoidance and complex multi-vehicle scenarios by breaking down the overall problem into manageable segments that can be processed independently and then integrated.
Solution Approach 2:
The centralized coordinated vehicle guidance system is designed to perform multiple functions: it can handle single vehicle-object avoidance, multi-vehicle collision prediction, near-parallel trajectory scenarios, and 3D space operations. This universal system replaces multiple specialized systems with one unified platform that adapts to various collision scenarios through configurable parameters and algorithms.
2Reliability
If centralized coordinated vehicle guidance system is implemented, then multiple vehicle collision prediction is achieved, but system complexity increases
Solution Approach 1:
The system merges individual vehicle guidance functions into a single centralized coordinated vehicle guidance system. By combining multiple independent guidance systems into one unified platform, the system achieves better multi-vehicle collision prediction through shared information and coordinated decision-making, while managing complexity through modular architecture and standardized interfaces.
Solution Approach 2:
The centralized system acts as an intermediary between individual vehicles and the collision avoidance function. Rather than each vehicle independently making avoidance decisions, the centralized system receives data from all vehicles, processes collision risks, and provides coordinated guidance commands, simplifying the overall system architecture while improving multi-vehicle scenario handling.
3Reliability
If trajectory adjustment is made to avoid collisions, then collision prevention is achieved, but fuel consumption and energy demand increase
Solution Approach 1:
The system performs preliminary collision prediction and trajectory adjustment planning before actual collision risk materializes. By detecting potential collisions early and making gradual trajectory adjustments in advance, the system prevents collisions while minimizing energy consumption compared to last-minute emergency maneuvers. The predictive nature allows for smooth, fuel-efficient course corrections.
Solution Approach 2:
The system optimizes trajectory adjustments by changing multiple parameters simultaneously (velocity, direction, acceleration profiles) rather than making large single-parameter changes. This allows for smoother, more fuel-efficient maneuvers that still achieve collision avoidance. The coordinated guidance system calculates optimal parameter changes that balance safety requirements with energy consumption constraints.
Data Source
AI summary
A computer-implemented method performed by a centralized coordinated vehicle guidance system may include: obtaining analytics data for a plurality of vehicles or objects centrally communicating with or detected by the centralized coordinated vehicle guidance system; detecting, based on the analytics data, a predicted collision event involving multiple pairs of the plurality of vehicles or objects; determining trajectory adjustment information for a first vehicle of the plurality of vehicles involved in the collision event; and outputting the trajectory adjustment information to cause the first vehicle to modify its trajectory.


