Scenario Engineering for Autonomous Transportation: A New Stage in Open-Pit Mines

IF 14 1区工程技术 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

IEEE Transactions on Intelligent Vehicles Pub Date : 2024-03-08 DOI:10.1109/TIV.2024.3373495

Siyu Teng;Xuan Li;Yuchen Li;Lingxi Li;Zhe Xuanyuan;Yunfeng Ai;Long Chen

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Abstract

In recent years, open-pit mining has seen significant advancement, the cooperative operation of various specialized machinery substantially enhancing the efficiency of mineral extraction. However, the harsh environment and complex conditions in open-pit mines present substantial challenges for the implementation of autonomous transportation systems. This research introduces a novel paradigm that integrates Scenario Engineering (SE) with autonomous transportation systems to significantly improve the trustworthiness, robustness, and efficiency in open-pit mines by incorporating the four key components of SE, including Scenario Feature Extractor, Intelligence and Index, Calibration and Certification, and Verification and Validation. This paradigm has been validated in two famous open-pit mines, the experiment results demonstrate marked improvements in robustness, trustworthiness, and efficiency. By enhancing the capacity, scalability, and diversity of autonomous transportation, this paradigm fosters the integration of SE and parallel driving and finally propels the achievement of the ‘6S’ objectives.

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自主运输的情景工程：露天矿的新阶段

近年来，露天采矿业取得了长足的进步，各种专用机械的协同作业大大提高了矿物开采的效率。然而，露天矿环境恶劣、条件复杂，给自主运输系统的实施带来了巨大挑战。本研究提出了一种将情景工程（SE）与自主运输系统相结合的新范例，通过结合情景工程的四个关键组成部分，包括情景特征提取器、智能与索引、校准与认证以及验证与确认，显著提高露天矿的可信度、稳健性和效率。这一范例已在两个著名的露天矿中得到验证，实验结果表明其在稳健性、可信度和效率方面都有明显改善。通过提高自主运输的能力、可扩展性和多样性，该范例促进了 SE 与并行驾驶的整合，并最终推动了 "6S "目标的实现。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Intelligent Vehicles Mathematics-Control and Optimization

CiteScore

12.10

自引率

13.40%

发文量

177

期刊介绍： The IEEE Transactions on Intelligent Vehicles (T-IV) is a premier platform for publishing peer-reviewed articles that present innovative research concepts, application results, significant theoretical findings, and application case studies in the field of intelligent vehicles. With a particular emphasis on automated vehicles within roadway environments, T-IV aims to raise awareness of pressing research and application challenges. Our focus is on providing critical information to the intelligent vehicle community, serving as a dissemination vehicle for IEEE ITS Society members and others interested in learning about the state-of-the-art developments and progress in research and applications related to intelligent vehicles. Join us in advancing knowledge and innovation in this dynamic field.