• Journal of Auto-vehicle Safety Association
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• v.16 no.2
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• pp.6-13
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• 2024

This paper presents a method of longitudinal motion planning of autonomous vehicles to deal with the non-signalized crosswalk environment. Based on the traffic laws, vehicles should slow down when passing the non-signalized crosswalk to prepare for situations where a nearby pedestrian starts to cross. If a pedestrian is in the crossing phase, vehicles should stop in front of the stop-line and wait until the pedestrian finishes the crossing maneuver. To realize these behaviors in autonomous vehicles, the driving mode and corresponding driving strategy are determined when vehicles encounter the crosswalk. The driving mode is determined according to the behavioral status of the nearby pedestrian. Longitudinal motion for the stopping or passing maneuver is planned according to the determined driving mode. The proposed algorithm has been validated via autonomous driving tests with our test vehicle in a real world. The test results show that the proposed algorithm enables the test vehicle to follow the traffic laws and behave safely against crossing pedestrians in the non-signalized crosswalk.

• Journal of Auto-vehicle Safety Association
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• v.15 no.4
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• pp.16-22
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• 2023

This paper presents a proactive longitudinal motion planning algorithm for improving the safety of an automated bus. Since the field of view (FOV) of the autonomous vehicle was limited depending on onboard sensors' performance and surrounding environments, it was necessary to implement vehicle-to-vehicle (V2V) communication for overcoming the limitation. After a virtual V2V-equipped target was constructed considering information obtained from V2V communication, the reference motion of the ego vehicle was determined by considering the state of both the V2V-equipped target and the sensor-detected target. Model predictive control (MPC) was implemented to calculate the optimal motion considering the reference motion and the chance constraint, which was deduced from manual driving data. The improvement in driving safety was confirmed through vehicle tests along actual urban roads.

• Journal of Auto-vehicle Safety Association
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• v.16 no.1
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• pp.6-11
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• 2024

This paper presents a motion planning algorithm of autonomous racing vehicles for mimicking the characteristics of a human driver. Time optimal maneuver of a race car has been actively studied as a major research area over the past decades. Although the time optimization problem yields a single time series solution of minimum time maneuver inputs for the vehicle, human drivers achieve similar lap times while taking various racing lines and velocity profiles. In order to model the characteristics of a specific driver and reproduce the motion, a stochastic motion planning framework based on kernelized motion primitive is introduced. The proposed framework imitates the behavior of the generated reference motion, which is based on a small number of human demonstration laps along the racetrack using Gaussian mixture model and Gaussian mixture regression. The mean and covariance of the racing line and velocity profile mimicking the driver are obtained by accumulating the outputs tested at equidistantly sampled input points. The results confirmed that the obtained lateral and longitudinal motion simulates the driver's driving characteristics, which are feasible for actual vehicle test environments.

• Radiation Oncology Journal
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• v.22 no.1
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• pp.55-63
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• 2004

Purpose : To evaluate the reflection of tumor motion according to the planning CT scan time. Material and Methods : A model of N-shape, which moved aiong the longitudinal axis during the ventilation caused by a mechanical ventilator, was produced. The model was scanned by planning CT, while setting the relative CT scan time (T: CT scan time/ventilatory period) to 0.33, 0.50, 0.67, 0.75, 1.00, 1.337, and 1.537. In addition, three patients with non-small cell lung cancer who received stereotactic radiosurgery In the Department of Radiation Oncology, Asan Medical Center from 03/19/2002 to 05/21/2002 were scanned. Slow (10 Premier, Picker, scan time 2.0 seconds per slice) and fast CT scans (Lightspeed, GE Medical Systems, with a scan time of 0.8 second per slice) were peformed for each patient. The magnitude of reflected movement of the N-shaped model was evaluated by measuring the transverse length, which reflected the movement of the declined bar of the model at each slice. For patients' scans, all CT data sets were registered using a stereotactic body frame scale with the gross tumor volumes delineated in one CT image set. The volume and three-dimensional diameter of the gross tumor volume were measured and analyzed between the slow and fast CT scans. Results : The reflection degree of longitudinal movement of the model increased in proportion to the relative CT scan times below 1.00 7, but remained constant above 1.00 T Assuming the mean value of scanned transverse lengths with CT scan time 1.00 T to be $100\%$, CT scans with scan times of 0.33, 0.50, 0.57, and 0.75 T missed the tumor motion by 30, 27, 20, and $7.0\%$ respectively, Slow (scan time 2.0 sec) and Fast (scan time 0.8 sec) CT scans of three patients with longitudinal movement of 3, 5, and 10 mm measured by fluoroscopy revealed the increases in the diameter along the longitudinal axis Increased by 6.3, 17, and $23\%$ in the slow CT scans. Conculsion : As the relative CT scan time increased, the reflection of the respiratory tumor movement on planning CT also Increased, but remained constant with relative CT scan times above 1.00 T When setting the planning CT scan time above one respiration period (>1.00 T), only the set-up margin is needed to delineate the planning target volume. Therefore, therapeutic ratio can be increased by reducing the radiation dose delivered to normal lung tissue.

• Journal of the Korean Institute of Navigation
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• v.1 no.1
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• pp.45-62
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• 1977

The advanced researches of the ship's motion in the seaway can predict the heaving, pitching and slamming of ship's motion. The researches as of today are that of displacement type such as a small typical fishing boat and U, UV and V bow ship forms under low speed. In recent day, the study of behaviours of high speed planning boat in the regular waves has been carried out by Bessho [5]. The calculation about behaviours of a high speed vessel in the longitudinal regular waves is calculated by Ordinary Strip Method in this paper. The data of the results were discussed and compared with Bessho's results. The conclusions deduced from this study are as follow, (1) The acceleration of motion calculated by the O.S.M. is similar with Bessho's data for the Fn 0.5 (2) The amplitudes of the behaviours of motions take peak at 1.0<λ/L<1.4.

• Journal of the Korean Institute of Navigation
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• v.3 no.2
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• pp.1-19
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• 1979

The advanced researches of the ship's motion in the seaway can predict the heaving, pitching and slamming of ship's motion. The researches as of today are that of displacement type such as a small typical fishing boat and U, UV and V bow ship forms under low speed. In recent day, the study of behaviours of high speed planning boat in the regular waves has been carried out by Bessho [5]. The calculation about behaviours of a high speed vessel in the longitudinal regular waves is calculated by Ordinary Strip Method in this paper. The data of the results were discussed and compared with Bessho's results. The conclusions deduced from this study are as follow, (1) The acceleration of motion calculated by the O.S.M. is similar with Bessho's data for the Fn 0.5 (2) The amplitudes of the behaviours of motions take peak at 1.0<λ/L<1.4.

• 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.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.14-19
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• 2022

This paper presents motion planning algorithm that yields to intervening side lane vehicles in a congested traffic flow based on vehicle to vehicle (V2V) communication. Autonomous driving in dense traffic situation requires advanced driving performance in terms of vehicle interaction and risk mitigation. One of the most important functions necessary for congested traffic autonomous driving is to predict the lane change intention of the side lane target vehicle. However, implementing this function by using only environmental sensors has limitations. In this study, V2V communication is used to overcome the limitations and determine the intention of cut-in vehicles. Lane change intention of the intervening side lane vehicle is inferred by its longitudinal speed, steering angle, and turn signal light information received by the on-board-unit (OBU). Once the yield decision is made, the subject vehicle decelerates to generate sufficient clearance for the target vehicle to enter. Validation of the algorithm was conducted with actual autonomous test vehicles.

• Radiation Oncology Journal
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• v.15 no.4
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• pp.387-392
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• 1997

Purpose : To quantify the movement of lung Parenchyma for ICRU 50 Planning Target Volume (PTV) delineation of the lung region. Materials and Method : Fluoroscopic observations and measurements are Performed on 10 patients with chest region cancer who have normal putmonary functions We have divided the lung region into 12 parts for the right lung, 10 parts for the left lung and four to five Points of lung parenchyma were selected for anatomical analysis Points, Fluoroscopic images are sent to a computer and then movements are measured. Results : Both lowe lobes showed the longest longitudinal movements because of breathing (average 14.1mm, maximum 22.1mm), while anteroposterior displacement showed the smallest value. Lateral movements of the lung parenchyma averaged 6.6mm, and the maximum value was 9.1mm, (both hilar regions showed maximum values because of cardiac motion) Conclusion : We could quantify the lung movements by measuring parenchyma displacements. The movements of both upper lobes were less than those of the middle and upper lobes in longitudinal and transverse movements. Optimal margins can be selected for PTV delineation using these results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.575-583
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• 2017

This paper describes the design and evaluation of a driving mode decision algorithm for automated driving for merge situations on highways. For the development of a highly automated driving control algorithm for merge situations, the driving mode decision is crucial for merging appropriately. There are two driving modes: lane keeping and lane changing (merging). The merge mode decision is determined based on the state of the surrounding vehicles and the remaining length of the merge lane. In the merge mode decision algorithm, merge possibility and the desired merge position are decided to change the lane safely and quickly. A safety driving envelope is defined based on the desired driving mode using the information on the surrounding vehicles' behaviors. To obtain the desired steering angle and longitudinal acceleration for maintaining the subject vehicle in the safe driving envelope, a motion planning controller is designed using model predictive control (MPC), with constraints that are decided considering the vehicle dynamics, safe driving envelope, and actuator limit. The proposed control algorithm has been evaluated via computer simulation studies.