煤矿井下网联式自动驾驶技术研究

李晨鑫; 张立亚

doi:10.13272/j.issn.1671-251x.17930

煤矿井下网联式自动驾驶技术研究

doi: 10.13272/j.issn.1671-251x.17930

李晨鑫^{1, 2, 3,},
张立亚^{1, 2, 3}

1.
煤炭科学技术研究院有限公司, 北京　100013
2.
煤矿应急避险技术装备工程研究中心, 北京　100013
3.
北京市煤矿安全工程技术研究中心, 北京　100013

基金项目: 天地科技股份有限公司科技创新创业资金专项项目（2022-TD-ZD001，2022-2-TD-ZD001）；煤炭科学技术研究院技术创新基金项目（2020CX- Ⅰ -10，2020CX- Ⅰ -11）。

详细信息

作者简介:
李晨鑫（1986-），男，河南永城人，副研究员，博士，研究方向为智能矿山通信技术，E-mail：ccrilichenxin@126.com

中图分类号: TD67
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- 被引次数: 0
出版历程
- 收稿日期: 2022-04-10
- 修回日期: 2022-06-12
- 网络出版日期: 2022-06-28

Research on the network connected automatic driving technology in underground coal mine

LI Chenxin^{1, 2, 3
,},
ZHANG Liya^{1, 2, 3}

1.
CCTEG China Coal Research Institute, Beijing 100013, China
2.
Engineering Research Center for Technology Equipment of Emergency Refuge in Coal Mine, Beijing 100013, China
3.
Beijing Engineering and Research Center of Mine Safe, Beijing 100013, China

摘要

摘要: 通过分析地面常规自动驾驶智能化和网联化技术发展现状及技术特点，结合煤矿井下无GNSS（全球卫星导航系统）信号覆盖、巷道照度低、遮挡物与障碍物较多、煤尘粉尘普遍存在的环境特点，提出了煤矿井下开展自动驾驶研究的关键技术，即无GNSS的移动高精定位技术、激光雷达技术、基于毫米波雷达的井下障碍物检测技术、井下低照度视频实时增强和特征匹配技术、井下环境高精地图技术、井下自动驾驶车辆决策规划技术、井下自动驾驶车辆控制执行技术、井下5G通信技术、C−V2X直连通信技术等；指出煤矿井下开展自动驾驶应用具有少人化/无人化需求显著、运营管理主体明确、场景封闭、路线固定、车速较慢、渗透率可控、5G建设基础较好、接口易开放等优势。构建了包括井下自动驾驶车辆、巷道基础设施、人员、煤矿云/边缘计算平台及煤矿自动驾驶应用服务平台的“人−车−巷−云”煤矿井下网联式自动驾驶系统参考架构，设计了包括感知定位系统、网联协同系统、车载操作系统、车辆基础组件的煤矿自动驾驶车辆架构，提出煤矿井下网联式自动驾驶演进将经历3个阶段：第1阶段为远程自动驾驶，实现车辆驾驶人员从井下到井上的转移；第2阶段为具有紧急接管边界的车辆自动驾驶，以车辆自动驾驶为主，将远程紧急接管作为安全保障手段；第3阶段为“人−车−巷−云”协同控制，井下自动驾驶车辆安全高效自主运行，实现高度无人化智能运输。
- 煤矿井下无人驾驶 /
- 自动驾驶 /
- 智能化 /
- 网联化 /
- 蜂窝车联网 /
- 5G /
- 高精感知定位 /
- 车巷协同
Abstract: This paper analyses the development status and technical characteristics of intelligent and networked technologies for conventional ground automatic driving. This paper also analyses the coal mine environmental characteristics, such as no GNSS (global navigation satellite system) signal coverage, low roadway illumination, lots of obstructions and obstacles and ubiquitous coal dust. In the context of the above technical and environmental characteristics, this study puts forward the key technologies of automatic driving research in underground coal mine. The technologies include mobile high-precision positioning technology without GNSS, laser radar technology, underground obstacle detection technology based on millimeter wave radar, underground low illumination video real-time enhancement and characteristic matching technology, underground environment high-precision map technology, underground autonomous vehicle decision planning technology, underground autonomous vehicle control execution technology, underground 5G communication technology and C-V2X direct connection communication technology. It is pointed out that the application of automatic driving in underground coal mine has the advantages of significant demand for fewer people or no people, clear operation management subject, closed scene, fixed route, slow speed, controllable permeability, good 5G construction foundation, easy open interface, etc. The reference architecture of 'human-vehicle-roadway-cloud' coal mine underground network connected automatic driving system is constructed. The system includes underground automatic driving vehicle, roadway infrastructure, personnel, coal mine cloud/edge computing platform and coal mine automatic driving application service platform. This paper designs the coal mine automatic driving vehicle architecture, which includes perception positioning system, network connected collaborative system, vehicle-mounted operating system and vehicle basic components. This paper puts forward three stages of the evolution of the network connected automatic driving in underground coal mines. The first stage is remote control and automatic driving, which realizes the transfer of vehicle drivers from underground to ground. The second stage is the automatic driving of vehicles with emergency takeover boundary. The vehicles are mainly driven by automatic driving, and remote emergency takeover is used as a safety guarantee method. The third stage is 'human-vehicle-roadway-cloud' collaborative control, the underground autonomous vehicles operate safely, efficiently and autonomously to realize highly unmanned intelligent transportation.
- unmanned driving in underground coal mine /
- automatic driving /
- intelligence /
- network connected /
- cellular vehicle-to-everything /
- 5G /
- high precision perception positioning /
- vehicle roadway collaboration

HTML全文

图 1 自动驾驶感知定位技术基本原理

Figure 1. Basic principle of perception positioning technology of automatic driving

下载: 全尺寸图片幻灯片

图 2 C−V2X通信接口

Figure 2. C-V2X communication interface

下载: 全尺寸图片幻灯片

图 3 煤矿井下网联式自动驾驶系统参考架构

Figure 3. Reference architecture of underground coal mine network connected and automatic driving system

下载: 全尺寸图片幻灯片

表 1 煤矿井下智能化、网联化关键技术

Table 1. Key technologies of underground intelligent technologies and network connected technologies

分类	细分技术	技术优势	需要研究或解决的技术问题
智能化	GNSS RTK	−	井下不可用，需要采用其他定位技术（如UWB）
	激光雷达	检测精度高，点云数据匹配计算量相对小	成本高，需要验证TOF激光雷达的多设备相互干扰情况、煤尘粉尘的干扰情况
	毫米波雷达	检测精度相对高，适用于障碍物检测	目前尚未发现公开的毫米波电磁成像地图产品
	摄像头	检测精度高，技术成熟	需要验证井下低照度环境的实时特征匹配性能
	高精地图	煤矿井下地图采集制作的限制条件少	需要建立井下地图采集制作的标准体系
	决策规划	煤矿井下可重用地面经典方法和机制	需要符合煤矿井下巷道特征
	控制执行	煤矿井下可重用地面经典方法和机制	线控、电子电气架构设计需符合煤矿安全要求
网联化	5G通信	煤矿5G建设和应用基础较好	上行资源紧张，依赖基站信号覆盖
网联化	C−V2X直连通信	专用频段上无系统间干扰，时延低，可靠性高	需要开展5.9 GHz频段传输特性研究，研究时间同步、应用层协议、业务与链路的映射与选择机制

下载: 导出CSV

表 2 3GPP TS22.186定义的车联网应用场景指标

Table 2. Application scene indicator of V2X defined in 3GPP TS 22.186

应用场景	时延/ms	可靠性/%	数据传输速率/(Mbit·s⁻¹)
远程驾驶	5	99.999	25(上行)
远程驾驶	5	99.999	1(下行)
车辆编队	10	99.99	65
高级自动驾驶	3	99.999	53
传感器数据共享	3	99.999	1000

下载: 导出CSV

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