Vehicle interactions remain a leading cause of serious injuries and fatalities in mining. The disparity between massive haul trucks and light vehicles or pedestrians means that collisions have severe consequences. Collision avoidance technology is providing additional protection.

The Scale of the Problem

Mining vehicles create unique hazards:

Size differential: A loaded haul truck can weigh over 500 tonnes. Light vehicles and personnel have no chance in a collision.

Visibility limitations: Large equipment has substantial blind spots. Operators simply cannot see everything around their vehicles.

Operating complexity: Multiple equipment types operate in confined spaces. Haul trucks, dozers, loaders, graders, and light vehicles share work areas.

Environmental factors: Dust, rain, darkness, and sun glare affect visibility. Conditions change throughout shifts.

Despite extensive training and procedures, incidents continue. Technology provides an additional layer of protection.

Detection Technologies

Collision avoidance systems use multiple sensing technologies:

Radar: Detects objects and measures distance and relative velocity. Works in dusty and dark conditions where cameras struggle.

GPS/GNSS: Tracks equipment positions precisely. Comparing positions identifies proximity risks.

RFID: Tags on personnel and light vehicles are detected by readers on heavy equipment. Provides identification alongside detection.

Cameras: Visual detection using computer vision. Can distinguish object types and identify personnel.

LiDAR: Laser scanning creates detailed 3D maps of surroundings. Detects obstacles with high precision.

Ultra-wideband (UWB): Provides precise ranging for close-proximity applications. Complements GPS for detailed positioning.

Most effective systems combine multiple technologies, using their complementary strengths.

System Capabilities

Modern collision avoidance systems provide graduated responses:

Zone definition: Systems define warning and critical zones around equipment. Zone sizes can vary by speed, direction, and equipment type.

Operator alerts: When other equipment or personnel enter warning zones, operators receive visual and auditory alerts. Alert urgency increases as proximity increases.

Intervention: When objects enter critical zones, systems can automatically intervene – reducing speed, applying brakes, or preventing movement.

Recording: Systems log all proximity events. Data supports investigation of incidents and identification of high-risk areas or behaviours.

Communication: Some systems communicate between vehicles, coordinating responses and sharing awareness.

Implementation Challenges

Deploying collision avoidance effectively requires addressing several challenges:

False alarms: Systems that alarm frequently without genuine risk desensitise operators. Calibration and zone design must minimise false positives.

Coverage gaps: Different technologies have different coverage patterns. Ensuring complete coverage around equipment requires careful sensor placement.

Mixed fleet: When equipment from different vendors operates together, system interoperability becomes essential.

Retrofit complexity: Existing equipment may be difficult to retrofit with comprehensive sensing and intervention capability.

Environmental performance: Systems must perform reliably in dust, rain, extreme temperatures, and electromagnetic interference.

Maintenance: Sensors and systems require ongoing maintenance. Degraded performance can create false confidence.

Regulatory Requirements

Regulators increasingly mandate collision avoidance:

Australian requirements: Various state regulators require proximity detection on heavy equipment, though requirements vary.

International standards: ISO and other bodies have developed standards for mining collision avoidance systems.

Site-specific requirements: Many operations implement standards exceeding regulatory minimums.

Requirements continue to evolve as technology improves and expectations increase.

Industry Experience

Operations implementing comprehensive collision avoidance report positive results:

Incident reduction: Significant decreases in vehicle interaction incidents following deployment.

Near-miss capture: Systems identify close calls that might not otherwise be reported, enabling learning and improvement.

Behavioural change: Knowing that proximity is monitored changes operator behaviour. People maintain greater clearances.

Investigation support: Recorded data enables detailed incident investigation and accurate understanding of events.

System Selection Considerations

Operations selecting collision avoidance systems should consider:

Detection capability: What technologies are used and what are their limitations?

Intervention capability: Can the system intervene automatically, or only alert?

Interoperability: Will the system work with all equipment on site?

Integration: Does the system integrate with fleet management and safety systems?

Scalability: Can the system accommodate future fleet changes and technology updates?

Support: What vendor support is available for deployment and ongoing operation?

Track record: What operational experience demonstrates system effectiveness?

Looking Forward

Collision avoidance technology continues to advance:

AI integration: Machine learning is improving object recognition and prediction of movement trajectories.

Autonomous integration: Collision avoidance is being integrated with autonomous equipment systems for comprehensive vehicle control.

V2X communication: Vehicle-to-everything communication enables broader awareness of surroundings.

Regulatory evolution: Requirements will continue to expand as technology capability increases.

Connected ecosystems: Future systems may share information across sites and companies, learning from collective experience.

The goal is eliminating vehicle interaction incidents entirely. Technology alone won’t achieve this – it must be combined with engineering controls, procedures, and culture. But collision avoidance systems are an increasingly important component of comprehensive safety approaches in mining.