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D'Amico, Tommaso

University of British Columbia

Autonomous vehicle technologies are yet to become a common commercial product for road vehicles, however their presence in open pit mines has been a reality for over 10 years. The technology is now past the early adoption phase with the biggest companies in the industry boasting over 100 active autonomous vehicles in operation. The technology has been proven to reduce fuel consumption, maintenance and operation costs and downtime with respect to manned operations in a range of open pit mine operation improving productivity by up to 30%. The move towards widespread adoption, however, comes with concerns of ease of implementation, security, and reliability at scale. Early developments of Autonomous Hauling Systems (AHS) were based in Wi-Fi; however, this technology was designed for office and domestic use, so its implementation in mining required increased complexity and adaptation to operate, raising many concerns for operation at large scale. In 2019, the use of mobile networks began being popularized for industrial use with the release of the 4.9G LTE protocol, facilitating the use of the technology for AHS applications. Since this change, AHS industry players have been shifting their systems to use the technology, and with the more recent releases of 5G, the improved performance is expected to bring further changes to the way these automations are implemented. The 5G protocol brings the use of Mobile Edge Computing (MEC) as part of its innovative sweep of technologies, moving computing from few large server farms to closer locations to the end users. This Thesis explores the development of a physical replica of an Autonomous Haling Vehicle (AHV), observing the developments of on-road vehicles to evaluate the use of new technologies and processes to improve current AHS technologies. The project is used as abasis to evaluate the use of 5G communication in comparison to its 4G LTE predecessor in different aspects of the driving process. The system used is based off the Robotics Operating System (ROS) and it the uses a set of sensors and LTE, 5G and mm-Wave communication modules incorporated in a 1:14 scale remote controlled hauling truck.

Text

2023-03-31

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/81070

Mining Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/