Scored Collision Region for Worksites
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Solution Overview
Problem
Existing collision avoidance systems at worksites, such as those described in U.S. Pat. No. 8,477,021, are inefficient in tracking multiple machines and providing timely proximity warnings, especially in environments with a large number of machines, leading to potential collisions due to computational delays.
Innovation Solution
A scored-based collision region of interest system that receives data on machine positions, speeds, and directions, determines a criticality score for each machine, selects a group of machines, and generates a spatial map excluding low-criticality machines to reduce computational effort and enhance collision detection efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all machines at a worksite are tracked and monitored for proximity warnings, then collision detection coverage is improved, but computational processing time increases excessively
Solution Approach 1:
The system segments the worksite into multiple zones and divides machine tracking into zone-specific subsets. Each zone has its own collision detection subsystem that processes only machines within that zone, rather than processing all machines globally. This segmentation reduces the computational burden on each processor while maintaining comprehensive coverage across the entire worksite.
Solution Approach 2:
The system applies partial action by selectively processing machine data based on relevance. It calculates proximity warnings only for machine pairs that are spatially close or have potential collision trajectories, rather than computing all possible machine combinations. This partial processing approach significantly reduces computational effort while maintaining adequate collision detection coverage.
2Reliability
If proximity warnings are provided for all machine combinations, then safety coverage is improved, but system complexity increases
Solution Approach 1:
The system applies local quality by providing different levels of monitoring intensity to different machine pairs based on their collision risk. High-risk machine combinations (e.g., opposing traffic directions, narrow clearance zones) receive continuous detailed monitoring, while low-risk combinations receive minimal or periodic monitoring. This differentiated approach maintains comprehensive safety coverage while reducing overall system complexity.
Solution Approach 2:
The system implements partial action by selectively generating proximity warnings only for machine pairs that meet specific collision risk criteria, rather than issuing warnings for all possible machine combinations. This selective warning generation reduces the complexity of warning management systems while maintaining adequate safety coverage.
Data Source
AI summary
Systems and methods for collision avoidance using scored-based collision region of interest are disclosed. One method includes receiving data relating to a plurality of machines disposed at a worksite, the data comprising at least one of a position, speed, and direction of movement for at least one machine of the plurality of machines; determining based at least on the data, a score for at least one machine of the plurality of machines, the score representing a criticality; based at least on the determined score, selecting, a group of machines from the plurality of machines; determining, a spatial map representing a position for at least one machine of the selected group of machines; and determining, based at least on the spatial map, a likelihood of collision for at least one machine of the selected group of machines.