• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.51-56
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• 2022

This paper presents an Ground Segmentation algorithm to eliminate unnecessary Lidar Point Cloud Data (PCD) in an autonomous driving system. We consider Random Sample Consensus (Ransac) Algorithm to process lidar ground data. Ransac designates inlier and outlier to erase ground point cloud and classified PCD into two parts. Test results show removal of PCD from ground area by distinguishing inlier and outlier. The paper validates ground rejection algorithm in real time calculating the number of objects recognized by ground data compared to lidar raw data and ground segmented data based on the z-axis. Ground Segmentation is simulated by Robot Operating System (ROS) and an analysis of autonomous driving data is constructed by Matlab. The proposed algorithm can enhance performance of autonomous driving as misrecognizing circumstances are reduced.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1060-1067
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• 2009

The selection and operation of tower cranes at construction sites are dependent on the personal experience of engineers in charge of lifting work. It often causes to overestimate the safety factor resulting in increase of construction cost, or underestimate it resulting in disastrous accident. Therefore, selection of tower cranes needs to consider cost, safety and maximum lifting condition. This study, for resolving such problems, was intended to propose the algorithm designed for even the inexperienced person to select the optimal lifting equipment in timely manner. The algorithm presented herein is an optimization algorithm that enables automatic arrangement of tower crane and minimization of costs by analyzing such conditions as vertical height and lifting load, etc.

• Journal of Auto-vehicle Safety Association
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• v.16 no.1
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• pp.29-34
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• 2024

This paper presents a multi-label lane detection method for autonomous vehicles based on deep learning. The proposed algorithm can detect two types of lanes: center lane and normal lane. The algorithm uses a convolution neural network with an encoder-decoder architecture to extract features from input images and produce a multi-label heatmap for predicting lane's label. This architecture has the potential to detect more diverse types of lanes in that it can add the number of labels by extending the heatmap's dimension. The proposed algorithm was tested on an OpenLane dataset and achieved 85 Frames Per Second (FPS) in end to-end inference time. The results demonstrate the usability and computational efficiency of the proposed algorithm for the lane detection in autonomous vehicles.

• Wind and Structures
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• v.24 no.3
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• pp.249-265
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• 2017

An efficient and accurate algorithm is proposed to estimate flutter safety factor of suspension bridges satisfying prescribed reliability levels. Uncertainties which arise from the basic wind speed at the bridge deck location, critical flutter velocity, the wind conversion factor from a scaled model to the prototype structure and the gust speed factor are incorporated. The proposed algorithm integrates the concepts of the inverse reliability method and the calculation method of the critical flutter velocity of suspension bridges. The unique feature of the proposed method is that it offers a tool for flutter safety assessment of suspension bridges, when the reliability level is specified as a target to be satisfied by the designer. Accuracy and efficiency of this method with reference to three example suspension bridges is studied and numerical results validate its superiority over conventional deterministic method. Finally, the effects of various parameters on the flutter safety factor of suspension bridges are also investigated.

• Journal of Auto-vehicle Safety Association
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• v.9 no.4
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• pp.32-37
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• 2017

For automated vehicles, the integrity and fault tolerance of environment perception sensor have been an important issue. This paper presents radar, vision, lidar(laser radar) fusion-based fault detection algorithm for autonomous vehicles. In this paper, characteristics of each sensor are shown. And the error of states of moving targets estimated by each sensor is analyzed to present the method to detect fault of environment sensors by characteristic of this error. Each estimation of moving targets isperformed by EKF/IMM method. To guarantee the reliability of fault detection algorithm of environment sensor, various driving data in several types of road is analyzed.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.649-658
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• 2009

The Aim of this development is the safety management network of embankment facilities using forecasting analysis algorism. Using this algorithm it is possible to predict a failure of embankment facilities in advance. therefore, it is necessary for making plans of a safety countermove. In this development we have researched the analysis method which could operate effectively the embankment facilities using real-time monitoring data from a remote sensing system and the safety managerial program using the algorithm from the analysis method developed.

• Journal of Radiation Industry
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• v.7 no.2_3
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• pp.121-126
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• 2013

The new algorithm technique is necessary to incorporate for analyzing and evaluating extreme condition like a nuclear accident. In this study, the combined methodology for measuring the three-dimensional space was compared with SIFT (Scale Invariant Feature Transform) and SURF (Speeded-Up Robust Feature) algorithm. The suggested method can be used for the acquisition of spatial information using the robot vision in the districted area of the nuclear facilities. As a result, these data would be helpful for identify the damaged part, degree of damage and determination of recovery sequences.

• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.37-42
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• 2019

This paper presents an autonomous acceleration planning algorithm for pedestrian collision avoidance at urban. Various scenarios between pedestrians and a vehicle are designed to maneuver the planning algorithm. To simulate the scenarios, we analyze pedestrian's behavior and identify limitations of fusion sensors, lidar and vision camera. Acceleration is optimally determined by considering TTC (Time To Collision) and pedestrian's intention. Pedestrian's crossing intention is estimated for quick control decision to minimize full-braking situation, based on their velocity and position change. Feasibility of the proposed algorithm is verified by simulations using Carsim and Simulink, and comparisons with actual driving data.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1047-1052
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• 2009

As buildings nowadays become taller in height and larger in size the safety review of lifting plan takes larger portion in construction project management. However, the cost and safety in lifting plan have a contradictory effect on each other. Therefore, an optimization algorithm needs devising as a solution of the contradictory problem. In many cases at construction sites, selections and stability review of tower cranes are assigned to equipment suppliers or field managers, which cause the problems in safety and cost of the projects. To improve the part of the current situation, a study on the optimization algorithm for designing the foundation of tower cranes is conducted in this study, which can be utilized by equipment suppliers or field managers to check the stability of tower cranes easily and promptly without substantial knowledge.

• Journal of Auto-vehicle Safety Association
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• v.16 no.2
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• pp.14-19
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• 2024

This paper describes autonomous emergency braking systems (AEB) for elderly drivers designed to consider their driving characteristics. With aging, perception-reaction time, and decision-making time increase accordingly. Without being aware of these performance degradations, however, changes in driving patterns due to increased alertness while driving lead to vehicle crashes. Therefore, it is necessary to develop an autonomous emergency braking system by incorporating the characteristics of the elderly driver. In order to enhance the driver acceptance of older people, perception-reaction time, alertness, and ride comfort need to be considered for conventional autonomous emergency braking systems (C-AEB). Proactive AEB(P-AEB) algorithm has been proposed to reflect human factor of elderly driver above. The performance of the proposed algorithm has been evaluated through MATLAB simulink simulation studies. It has been shown from the computer simulations that the proposed P-AEB algorithm enhances the driver acceptance of older people by improving ride comfort while ensuring safety of vehicle.