Real-Time Scheduling of Autonomous Mining Trucks via Flow Allocation-Accelerated Tabu Search

doi:10.1109/TIV.2022.3166564

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进机器人控制团队

	Real-Time Scheduling of Autonomous Mining Trucks via Flow Allocation-Accelerated Tabu Search
	Zhang, Xiaotong 7; Guo, Ao 6; Ai, Yunfeng 2,3; Tian, Bin 3,4,5; Chen, Long 1,3,4
刊名	IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
	2022-09-01
卷号	7 期号:3 页码:466-479
关键词	Mathematical models Fuels Autonomous vehicles Real-time systems Dynamic scheduling Load modeling Transportation Autonomous truck heuristic algorithm open-pit mine real-time scheduling
ISSN号	2379-8858
DOI	10.1109/TIV.2022.3166564
通讯作者	Chen, Long(long.chen@ia.ac.cn)
英文摘要	Material transportation is an essential process in mining operations and accounts for a large portion of total energy consumption. With the development of automation technology, autonomous mining trucks have been deployed in open-pit mines to reduce transportation costs. Compared to manned mining trucks, autonomous trucks are more appropriate for automatic scheduling techniques due to their high informatization, high-precision perception, and sophisticated control. However, the existing truck scheduling research does not exploit autonomous trucks' strengths to perform more delicate control, but still takes a traditional approach toward autonomous trucks. In this paper, we propose a mixed-integer programming model for joint optimization of autonomous trucks trips and speeds to minimize energy consumption. To solve the proposed scheduling model, a novel tabu search algorithm is proposed, which consists of two parts: an improved flow allocation model with matching factor is formulated in the upper part to determine the optimal truck flow, and in the lower part a tabu search procedure guided with the optimal flow is developed. Based on the mathematical model and solution technique, we also propose a real-time scheduling system of autonomous trucks for the stochastic and dynamic mining environment. A coal mine in Inner Mongolia, China, for example, we verified the effectiveness of the proposed truck scheduling model and real-time scheduling approach. We demonstrate that the proposed allocation model effectively accelerates the tabu search procedure, and for short-term decisions, the proposed solution technique satisfies the computational requirements of the real-time scheduling system.
资助项目	National Key Research and Development Program of China[2018YFB1305002] ; Key Research and Development Program of Guangzhou[202007050004]
WOS关键词	OPTIMIZATION ; CONSUMPTION ; SYSTEM
WOS研究方向	Computer Science ; Engineering ; Transportation
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000873905600010
资助机构	National Key Research and Development Program of China ; Key Research and Development Program of Guangzhou
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/50553]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者	Chen, Long
作者单位	1.Minist Emergency Management, Key Lab Intelligent Min & Robot, Beijing 100012, Peoples R China 2.Univ Chinese Acad Sci, Artificial Intelligence Dept, Beijing 100049, Peoples R China 3.Waytous Inc, Qingdao 266109, Shandong, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 6.Univ New South Wales, Sch Comp Sci & Engn, Sydney, NSW 2052, Australia 7.Sun Yat Sen Univ, Sch Comp Sci & Engn, Guangzhou 510275, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Xiaotong,Guo, Ao,Ai, Yunfeng,et al. Real-Time Scheduling of Autonomous Mining Trucks via Flow Allocation-Accelerated Tabu Search[J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,2022,7(3):466-479.
APA	Zhang, Xiaotong,Guo, Ao,Ai, Yunfeng,Tian, Bin,&Chen, Long.(2022).Real-Time Scheduling of Autonomous Mining Trucks via Flow Allocation-Accelerated Tabu Search.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,7(3),466-479.
MLA	Zhang, Xiaotong,et al."Real-Time Scheduling of Autonomous Mining Trucks via Flow Allocation-Accelerated Tabu Search".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 7.3(2022):466-479.