Implementing autonomous haulage trucks in mining: Safety benefits and management challenges

The mining industry continues to face persistent safety challenges, with powered haulage incidents remaining a leading cause of occupational fatalities. This study investigates the implementation of Autonomous Haulage Systems (AHS) in mining operations, focusing on their potential to enhance safety performance and the managerial complexities that accompany their deployment. Employing a qualitative analytical approach supported by industry case studies and empirical observations, the research evaluates how AHS integrating artificial intelligence (AI), global positioning systems (GPS), and advanced sensor technologies reduces human exposure to hazardous environments and mitigates accidents resulting from fatigue and operational error. Evidence from autonomous operations at Rio Tinto and Resolute Mining demonstrates substantial safety and efficiency gains, including zero lost-time injuries, a 15% reduction in unit costs, and increased operational uptime. Despite these advantages, AHS adoption introduces significant managerial challenges encompassing workforce transition, regulatory compliance, cybersecurity vulnerability, and system reliability. The findings underscore that the successful integration of AHS necessitates comprehensive management frameworks emphasizing employee retraining, adherence to international safety standards, proactive cybersecurity measures, and preventive maintenance systems. The study concludes that AHS represents a transformative technological innovation with the capacity to redefine safety management and operational efficiency in the mining sector. However, its long-term sustainability relies on the alignment of technological advancement with strategic management practices and organizational adaptability.