EACON no safety driver AHS at Norton Gold Fields: haulage design notes for engineers
Reviewed by Tom Sullivan

First reported on International Mining – News
30 Second Briefing
An autonomous Komatsu HD1500 haul truck at Zijin Mining-owned Norton Gold Fields in Western Australia has completed its first fully autonomous test cycle with no safety driver on board, using EACON Mining Technology’s autonomous haulage system (AHS) in partnership with Thiess. The milestone confirms driverless operation from loading to dumping under site conditions, moving a 142 t-class rigid truck on a fixed haul route without human intervention in the cab. For mine planners and fleet engineers, this marks progression from supervised trials to true unmanned haulage, enabling redesign of traffic management, interaction zones, and shift deployment.
Technical Brief
- Removal of the in-cab safety driver shifts critical controls to control-room supervision and field spotters during trials.
- Fixed-route testing constrains interactions with manned fleets, simplifying collision-avoidance validation and procedural training.
- For other mining sites, such no-driver cycles are a prerequisite before scaling to multi-truck autonomous fleets.
Our Take
Western Australia gold operations like Norton Gold Fields and Capricorn Metals’ Karlawinda/Yalgoo portfolio are increasingly prominent in our database as testbeds for new operating models, suggesting the region’s mature permitting and contractor ecosystem is well suited to early adoption of autonomous haulage.
For Zijin Mining, incremental autonomy at an Australian gold asset diversifies its technology exposure beyond its core Chinese base, which may help de‑risk future automation rollouts across its broader portfolio where regulatory and labour conditions differ.
Within the 890 tag-matched pieces that include safety, only a small subset combine safety with product and project tags in gold, so EACON’s driverless AHS testing positions it in a relatively small peer group where OEMs are using live gold operations to validate commercial-ready autonomy stacks.
Prepared by collating external sources, AI-assisted tools, and Geomechanics.io’s proprietary mining database, then reviewed for technical accuracy & edited by our geotechnical team.
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