Research on the intelligent management system of the trackless rubber-tyred vehicles in the coal mine
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摘要: 针对煤矿井下工作地点分散、运输路线复杂、巷道内弯道和交叉路口较多的特点与煤矿智能化建设的需要，从需求分析、系统架构、关键技术等方面对矿井无轨胶轮车智能化管理系统进行了研究。通过需求分析，得出矿井无轨胶轮车智能化管理系统需具有矿井车辆精准定位、矿井车辆工况信息实时采集、矿井车辆移动通信、矿井车辆智能导航、矿井车辆状态实时监测与控制、矿井车辆防碰撞预警等功能。对系统关键技术进行了详细介绍：分析了UWB定位技术在矿井无轨胶轮车定位中的应用；提出矿井车辆移动通信技术宜采用WiFi与4G/5G技术；讨论了常用路径规划技术的特点，得出矿井无轨胶轮车导航技术宜采用成熟度较高的基于图搜索的路径规划算法，矿井无轨胶轮车导航和轨迹回放技术应与GIS技术相结合；研究了矿井车辆红绿灯控制技术，提出了十字交叉口模型和单车通行巷模型；研究了车辆防碰撞预警技术，根据行人和车辆位置及其与UWB基站的相对方向和距离，分析了同基站与跨基站2种模式下的防碰撞预警原理。实验结果表明，基于UWB的矿井车辆通信、基于A*算法的矿井车辆路径规划及轨迹回放、红绿灯控制、防碰撞预警等功能均能满足应用需求。Abstract: In the coal mine, underground working places are scattered, transportation routes are complex, and there are many bends and intersections in the roadway. Based on the above characteristics and the needs of intelligent construction of coal mines, the intelligent management system of trackless rubber-tyred vehicles in coal mines is studied from the aspects of demand analysis, system architecture and key technologies. Through demand analysis, it is concluded that the intelligent management system of mine trackless rubber-tyred vehicles should have the functions of precise positioning of mine vehicles, real-time collection of mine vehicle working conditions information, mine vehicle mobile communication, mine vehicle intelligent navigation, real-time monitoring and control of mine vehicle status and mine vehicle anti-collision warning. The key technologies of the system are introduced in detail. The application of UWB positioning technology in mine trackless rubber-tyred vehicle positioning is analyzed. It is suggested that the mobile communication technology of mine vehicles should adopt WiFi and 4G/5G technology. The characteristics of common path-planning technology are discussed. It is concluded that the mine trackless rubber-tyred vehicle navigation technology should adopt the path planning algorithm based on graph search with high maturity. The mine trackless rubber-tyred vehicle navigation and track playback technology should be combined with GIS technology. The traffic light control technology of mine vehicles is studied. The intersection model and single-vehicle passing lane model are proposed. The vehicle anti-collision warning technology is studied. According to the position of pedestrians and vehicles and the relative direction and distance between them and the UWB base station, the anti-collision early warning principle under the two modes of the same base station and the cross-base station is analyzed. The experimental results show that the mine vehicle communication based on UWB, mine vehicle path planning and vehicle track playback based on A* algorithm, traffic light control, anti-collision early warning and other functions can meet the application requirements.
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图 1 矿井无轨胶轮车智能化管理系统架构
Figure 1. Architecture of intelligent management system of mine trackless rubber-tyred vehicle
图 2 基于TW−TOF的测距原理
Figure 2. Distance measuring principle based on two way-time of flight
表 1 常用路径规划算法优缺点
Table 1. Advantages and disadvantages of common path planning algorithms
分类 算法 原理 优点 缺点 基于图搜索的
路径规划算法Dijkstra算法 将路径网络中节点分为已分配节点组与未分配节点组，
并按照递增顺序生成一条最短路径路径短 无连续曲率 A*算法 与Dijkstra算法相比，该算法在引入新节点时，将已分配
节点的信息引入评价标准，提高搜索效率速度快 无连续曲率 基于采样的
路径规划算法概率路线图法 确定起始位置和目标位置后，根据训练好的离线阶段路
线图，使用启发式路径搜索算法确定一条可行路径速度快，
适合复杂场景无连续曲率 快速搜索
随机树法首先构建环境地图规划空间，然后将规划空间的起点作
为根节点，逐渐增加叶节点，生成随机扩展树，当随机扩
展树的叶节点到达目标节点所在区域时结束适合复杂场景 需进行优化 智能仿生算法 遗传算法 通过不同编码方式、变异算子及交叉算子的组合，模拟
自然进化过程，搜索路径的最优解空间适应能力强 计算成本高 蚁群优化算法 基于蚁群行为表现出的信息正反馈现象，生成一条初始
节点到目标节点的最短路径鲁棒性强 收敛速度慢 
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表 2 矿井车辆定位实验数据
Table 2. Experimental data of mine vehicle positioning
m 实验
类型基站
位置实际位置 测量位置 误差 静态
测量3206运输巷绕道口 +200 +200.20 0.20 3号永久避难硐室口 +150 +149.90 0.10 3306回风巷绕道口 +50 +50.25 0.25 动态
测量3206运输巷绕道口 +230 +235.25 5.25 3号永久避难硐室口 +180 +175.30 4.70 3306回风巷绕道口 +80 +86.80 6.80
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表 3 路径信息对比
Table 3. Comparison of path information
路径
类型起始
位置目标
位置路径信息 导航
路径清煤斜巷 3号永久避难硐室 清煤斜巷→检修硐室下200 m→3号联巷→3号联巷下150 m→管子道口→2号永久避难硐室→1号辅助水仓口→辅助巷配电点→3206运输巷绕道口→3号永久避难硐室 实际
路径清煤斜巷 3号永久避难硐室 清煤斜巷→检修硐室下200 m→3号联巷→3号联巷下150 m→管子道口→2号永久避难硐室→1号辅助水仓口→辅助巷配电点→3206运输巷绕道口→3号永久避难硐室
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表 4 单车通行巷实验数据
Table 4. Experimental data of single vehicle passing lane
行驶方向 基站 车辆位置/m HA状态 HB状态 基站A→基站B A −180 绿 绿 −195 绿 红 B 192 绿 红 175 绿 绿 基站B→基站A B 180 绿 绿 195 红 绿 A −195 红 绿 −185 绿 绿
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表 5 防碰撞预警实验数据
Table 5. Data sheet of anti-collision early warning experiment
实验
类型预警
类型车辆
位置/m行人或
车辆位置/m是否
预警同基站 行人与车辆 +200 +225 是 +20 −8 是 +200 +232 否 车辆
之间+180 +135 是 +200 +266 否 +30 −14 是 跨基站 行人与车辆 +390 −385 是 +380 −385 否 +395 −380 是 车辆
之间+380 −378 是 +390 −350 否 +380 −375 是
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