## 1 Introduction  
Autonomous driving technology enables vehicles to automatically drive to a desired point by recognizing and judging the driving environment. Recently, autonomous driving technology has been applied to mobile robots and is being used in fields such as manufacturing [1], logistics [2], and national defense [3]. Many studies [4; 5; 6; 7; 8; 9; 10; 11; 12] have been conducted to implement high-level autonomous driving technology in these fields. For example, [PERSON] et al. [13] tested various tasks in a manufacturing environment using autonomous mobile robots equipped with wheel encoders, cameras, light detection and ranging (LiDAR), and robot arms. [PERSON] and [PERSON] [14] developed an autonomous driving robot for logistics using an infrared sensor, encoder, global positioning system (GPS), ultrasonic sensor, navigation, path planning, and information fusion functions. [PERSON] et al. [15] developed a military autonomous driving robot equipped with a laser scanner, GPS, and camera. In the mining industry, several studies of autonomous driving technology have been conducted in underground mining environments using autonomous robots [16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26]. [PERSON] et al. [27] developed \"grounding\", an autonomous driving robot that can be used even in underground mines having poor road conditions. The autonomous driving robot was able to recognize the surrounding environment through the fusion of multiple sensors, perform tasks such as tunnel mapping, and return to the starting point. Field driving tests were performed in an abandoned mine environment using the developed autonomous driving robot, and stable driving performance was confirmed. [PERSON] [28] used an autonomous robot to estimate real-time location in an underground mining environment, performed 2D and 3D tunnel mapping work, and evaluated its accuracy. Recently, studies have been conducted on the use of autonomous robots with camera sensors for underground mining [29; 30]. [PERSON] et al. [31] developed an autonomous driving robot to perform initial exploration work in case of a human accident in an underground coal mine. In addition to being capable of autonomous driving, the developed robot can be remote controlled, and is equipped with a toxic gas detection sensor, camera sensor, and long-distance wireless communication router; furthermore, the operator can check the driving environment in real time using a camera. [PERSON] et al. [32] performed 3D tunnel mapping for an underground mine tunnel using mobile robots and a depth camera that can recognize 3D views. [PERSON] et al. [33] developed a real-time localization system in an underground mine using an autonomous driving loader for underground mining and a camera sensor. The developed localization system was able to perform accurate localization by integrating image processing technology and simultaneous localization and mapping. As aforementioned, most previous studies using autonomous robots in underground mines involved autonomous driving along only certain straight paths in underground mine tunnels. However, in a real underground mining environment, autonomous driving in a straight tunnel section as well as path planning technology to drive, for example, in a planned direction on a two-way road or returning after arriving at a turning point, are required. In addition, in underground mines, the shape of the tunnel is frequently changed by the blasting of the tunnel for mining minerals, making it difficult to effectively utilize the route planning technology using the global map surveyed in advance. Therefore, to improve the utilization of autonomous robots for underground mining, technologies for efficiently recognizing road signs using a camera sensor-based vision system and driving along a planned route in an underground mine without a global map should be developed.