Projected Zone Overlap Detection for Mining Vehicle Collision Avoidance
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Solution Overview
Problem
In mining environments, particularly open pit surface mining, large vehicles like mine haul trucks and shovels face challenges with blind spots and poor visibility, leading to potential collisions and inefficiencies due to current navigation systems being inaccurate and prone to false alarms, which can cause unnecessary braking and delays.
Innovation Solution
A system that uses location sensors and processors to project spatial zones around vehicles based on their current and historical movement data, alerting operators to potential collisions by indicating overlaps with other vehicles' projected zones, thereby enhancing navigation and reducing contention risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current navigation systems are used to track vehicle positions, then vehicle location can be monitored, but false alarms occur leading to unnecessary braking and delays
Solution Approach 1:
The system performs preliminary action by projecting the future path of travel of vehicles based on their current speed and historical path data before potential collisions occur. This allows the system to predict and prepare for potential collisions in advance, rather than reacting to false alarms after they are generated, thereby reducing unnecessary braking and delays while maintaining accurate vehicle location monitoring.
2Reliability
If projected zones are extended further to account for large vehicle sizes and slow braking capabilities, then collision prediction accuracy improves, but the complexity of the navigation system increases
Solution Approach 1:
The system applies dynamics by making the projected zone distance dynamic rather than static. The projected zone is extended by a distance determined by the current speed of the vehicle, meaning the zone automatically adjusts based on real-time operating conditions. This dynamic approach improves collision prediction accuracy for large vehicles with slow braking capabilities while avoiding the need for overly complex fixed-zone configurations.
3Reliability
If the projected zone distance is increased to account for slow braking capabilities of large vehicles, then collision detection reliability improves, but false alarm frequency increases
Solution Approach 1:
The system changes parameters by using the current speed of the vehicle as a variable parameter to determine the projected zone extension distance. This parameter-based approach allows the system to maintain reliable collision detection for large vehicles with slow braking capabilities while reducing false alarms, as the zone is neither excessively large nor too small but appropriately scaled to actual vehicle operating conditions.
Data Source
AI summary
A system and method for zone projection are presented. Specifically, anticipated paths of travel are determined for a number of different vehicles operating within an environment. Based upon those anticipated paths of travel, as well as likely stopping distances of each vehicle, the system generate zones around each vehicle. These projected zones define a geographical region into which each vehicle is likely to proceed as it maneuvers about the environment. With the zones determined, the system is configured to detect zones that overlap, and, when such overlapping zones are detected, can generate an alarm warning of a potential collision condition that may exist between the two corresponding vehicles.