• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.119-126
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• 2022

This paper presents a method to reduce the vibration-induced noise effect of an inertial measurement device mounted on a self-driving vehicle. The inertial sensor used in the GNSS/INS integrated navigation system of a self-driving vehicle is fixed directly on the chassis of vehicle body so that its navigation output is affected by the vibration of the vehicle's engine, resulting in the degradation of the navigational performance. Therefore, these effects must be considered when mounting the inertial sensor. In order to solve this problem, this paper proposes to use an in-house manufactured vibration suppression device and analyzes its impact on reducing the vibration effect. Experimental test results in a static scenario show that the vibration-induced noise effect is more clearly observed in the lateral direction of the vehicle, but can be effectively suppressed by using the proposed vibration suppression device compared to the case without it. In addition, the dynamic positioning test scenario shows the position, speed, and posture errors are reduced to 74%, 67%, and 14% levels, respectively.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.245-254
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• 2022

Sensor dataset for autonomous driving is one of the essential components as the deep learning approaches are widely used. However, most driving datasets are focused on typical environments such as sunny or cloudy. In addition, most datasets deal with color images and lidar. In this paper, we propose a driving dataset with multi-spectral images and lidar in adverse weather conditions such as snowy, rainy, smoky, and dusty. The proposed data acquisition system has 4 types of cameras (color, near-infrared, shortwave, thermal), 1 lidar, 2 radars, and a navigation sensor. Our dataset is the first dataset that handles multi-spectral cameras in adverse weather conditions. The Proposed dataset is annotated as 2D semantic labels, 3D semantic labels, and 2D/3D bounding boxes. Many tasks are available on our dataset, for example, object detection and driveable region detection. We also present some experimental results on the adverse weather dataset.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.419-426
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• 2008

As pulse detonation engine(PDE) does not need compression mechanisms such as compressors because self-sustained detonation waves are able to compress propellant gases by their incident shock waves, the PDE can have a simple straight-tube structure. In this study, we propose an autonomous driving valve system of the PDE, which fill premixed gases into the PDE tubes at high frequency with high mass flow rate. The proposed valve is composed of only three parts: a piston, a cylinder, and a spring. This valve system can produce intermittent flow at high mass flow rate, and also can keep stable reciprocal motion by using the propellant-gas enthalpy. When the cylinder content product is assumed to be constant, experimental results of the mass flow rate were approximately equal to the calculation model. We confirmed the autonomous driving valve performance by experiments, and concluded that this extremely simple valve with no electrical power and controller can be used as the PDE propellant supply system.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.121-128
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• 2000

In this paper, the control algorithm fur an autonomous vehicle is studied and applied to an actual 2 wheel-driven vehicle system. In order to control a nonholonomic system, the kinematic model for an autonomous vehicle is constructed by relative velocity relationship about the virtual point at distance from the vehicle's frame. And the optimal controller that based on the kinematic model is operated on purpose to track a reference vehicle's path. The actual system is designed with named 'HYAVI' and the system controller is applied. Because all the results of simulation don't satisfy the driving conditions of HYAVI, a reformed control algorithm that satisfies an actual autonomous vehicle is applied at HYAVI. At the results of actual experiments, the path tracking works very well by the reformed control algorithm. An autonomous vehicle that applied this control algorithm can be easily used for a path generation algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.313-330
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• 2021

In an autonomous driving system equipped with a camera and lidar, depth completion techniques enable dense depth estimation. In particular, using self-supervised learning it is possible to train the depth completion network even without ground truth. In actual autonomous driving, such depth completion should have very short latency as it is the input of other algorithms. So, rather than complicate the network structure to increase the accuracy like previous studies, this paper focuses on network latency. We design a U-Net type network with RegNet encoders optimized for GPU computation. Instead, this paper presents several techniques that can increase accuracy during the process of self-supervised learning. The proposed techniques increase the robustness to unreliable lidar inputs. Also, they improve the depth quality for edge and sky regions based on the semantic information extracted in advance. Our experiments confirm that our model is very lightweight (2.42 ms at 1280x480) but resistant to noise and has qualities close to the latest studies.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.90-98
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• 2020

Modern vehicles are evolving from manual to automatic driving. As the ratio of electrical equipment and software increases inside the vehicle, vehicles that support autonomous driving are becoming another open computer system that can communicate with the outside. The safety of the vehicle means the safety of both the passenger and the non-passenger. It is not clear whether the safety problem of ultimate autonomous vehicles can be solved by the current solution of computer systems related to fault tolerance and security. Autonomous vehicles should not be dangerous to people after they are released to the market, so it is necessary to proactively diagnose all the risks that can be predicted with current technology. This paper examines the current developments of autonomous vehicles and analyzes their dangers that threaten driving safety, as well as their countermeasures.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.95-100
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• 2019

In this paper, autonomous vehicles of service with existing vehicle accident for the prevention of the vehicle communication technology, self-driving techniques, brakes automatic control technology, artificial intelligence technologies such as well and developed the vehicle accident this occur to death or has been techniques, can prepare various safety cases intended to minimize the injury. In this paper, it is a study to secure safety in autonomous vehicles. This is determined according to spatial factors such as chip signals for general low-power short-range wireless communication and micro road AI. On the other hand, in this paper, the safety of boarding is improved by checking the signal from the electronic chip, up to "recognition of the emotion from residence time in the sensing area" to the biological electronic chip. As a result of demonstrating the reliability of the world countries the world, inducing safety autonomous system of all passengers in terms of safety. Unmanned autonomous vehicle riding and commercialization will lead to AI systems and biochips (Verification), linked IoT on the road in the near future, and the safety technology reliability of the world will be highlighted.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.464-470
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• 2021

Automobiles have been used as simple means of transportation, but recently, as automobiles are rapidly becoming intelligent and smart, and automobile preferences are increasing, research on IT technology convergence is underway, requiring basic high-performance functions such as driver's convenience and safety. As a result, autonomous driving and semi-autonomous vehicles are developed, and these technologies sometimes deviate from lanes due to environmental problems, situations that cannot be judged by autonomous vehicles, and lane detectors may not recognize lanes. In order to improve the performance of lane departure from the lane detection system of autonomous vehicles, which is such a problem, this paper uses fast recognition, which is a characteristic of YOLO(You only look once), and is affected by the surrounding environment using CSI-Camera. We propose a lane detection system that recognizes the situation and collects driving data to extract the region of interest.

• Journal of Auto-vehicle Safety Association
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• v.15 no.4
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• pp.23-31
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• 2023

In recent years, the technology for autonomous driving has been advancing rapidly, ADAS (Advanced Driver Assistance System) functions, which improve driver convenience and safety performance, are mostly equipped in recently released vehicles and range from level 0 to level 2 in autonomous driving technology. Among the various functions of ADAS, AEBS (Autonomous Emergency Braking System), which analyzes traffic accidents, is the most closely related to the vehicle's braking. This study developed a simulation technique for reproducing accidents related to AEBS based on real vehicle experimental data, and it was applied to the analysis of actual ADAS vehicle accidents to identify the causes of accidents.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.929-933
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• 2007

Concrete Pavement Cutting Operation have Labor-intensive features. And Cutting Operation quality and productivity is influenced by operator's experience. Moreover Workers have risk of safety concerns. Therefore we need Concrete Pavement Cutting Operation automation system and system support software development on the economics. First of all we have to develop driving Path Planning for Concrete Pavement Cutting automation system. If result of Path Planning connect with automation system, Weak points is a complement to the existing Path Planning and we can obtain effective automation system. Consequently this paper suggest method of Autonomous Driving Path Planning for Concrete Pavement Cutting Operation And the Path Planning system application.