• Science of Emotion and Sensibility
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• v.23 no.3
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• pp.3-10
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• 2020

This study is aimed at investigating drivers' reactions to yellow signal dilemma situations as a result of the existing signal system, and developing a new signal system. A driver-centered coping model was developed through bio-signal analysis. The driver's physiological response in the existing signal system was observed, and the signal system was developed by applying intersection road driving conditions using a car graphic simulator. Participants were classified into a control group (existing signal system) and an experimental group for a new yellow signal system (new signal system). Based on the results, the emergence of parasympathetic nerves was higher in the experimental group than in the control group, where a statistically significant difference was observed (p < 0.05). The newly developed signal system appeared to cause tension among drivers; however, the sympathetic to parasympathetic nerve ratio was 6: 4, which could be interpreted as an ideal balance. We conclude that drivers can drive more stably if the coping signal system developed in this study is applied to the traffic system.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1088-1095
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• 2009

In this paper, we describe the reorientation method of distorted road sign by using projection transformation for improving recognition rate of road sign. RSR (Road Sign Recognition) is one of the most important topics for implementing driver assistance in intelligent transportation systems using pattern recognition and vision technology. The RS (Road Sign) includes direction of road or place name, and intersection for obtaining the road information. We acquire input images from mounted camera on vehicle. However, the road signs are often appeared with rotation, skew, and distortion by perspective camera. In order to obtain the correct road sign overcoming these problems, projection transformation is used to transform from 4 points of image coordinate to 4 points of world coordinate. The 4 vertices points are obtained using the trajectory as the distance from the mass center to the boundary of the object. Then, the candidate areas of road sign are transformed from distorted image by using homography transformation matrix. Internal information of reoriented road signs is segmented with arrow and the corresponding indicated place name. Arrow area is the largest labeled one. Also, the number of group of place names equals to that of arrow heads. Characters of the road sign are segmented by using vertical and horizontal histograms, and each character is recognized by using SAD (Sum of Absolute Difference). From the experiments, the proposed method has shown the higher recognition results than the image without reorientation.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.7
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• pp.734-741
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• 2009

A new localization algorithm is proposed for a fast moving mobile robot, which utilizes only one beacon and the global features of the differential-driving mobile robot. It takes a relatively long time to localize a mobile robot with active beacon sensors since the distance to the beacon is measured by the traveling time of the ultrasonic signal. When the mobile robot is moving slowly the measurement time does not yield a high error. At a higher mobile robot speed, however, the localization error becomes too large to locate the mobile robot. Therefore, in high-speed mobile robot operations, instead of using two or more active beacons for localization, only one active beacon and the global features of the mobile robot are used to localize the mobile robot in this research. The two global features are the radius and center of the rotational motion for the differential-driving mobile robot which generally describe motion of the mobile robot and are used for the trace prediction of the mobile robot. In high speed operations the localizer finds an intersection point of this predicted trace and a circle which is centered at the beacon and has the radius of the distance between the mobile robot and the beacon. This new approach resolves the large localization error caused by the high speed of the mobile robot. The performance of the new localization algorithm has been verified through the experiments with a high-speed mobile robot.

• The KIPS Transactions:PartD
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• v.12D no.1 s.97
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• pp.21-30
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• 2005

In mobile computing environments, a mobile host caches the data to use the narrow bandwidth efficiently and improve the response time. A server periodically broadcasts the update data for maintaining the cache consistency of a mobile host. However, a method for maintaining cache consistency using periodic invalidation report has a problem that defers the commit decision of a mobile transaction to guarantee its serializable execution. In this paper, we propose CCM-AD method that guarantees the serializable execution of a mobile transaction even in the case that it is executed using cached data. As CCM-AD method guarantees the serializable execution of mobile transactions by using the intersection between the data broadcast to mobile host and the data updated at server. Then the CCM-AD method can reduce the delay of commitment decision of a mobile transaction. Also our method can reduce the size of invalidation report.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.300-309
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• 2003

The Japanese developed the first Car navigation system in 1981 with the advent of Honda, which was known as the car inertial navigation system. Now days, It is possible to search the shortest route to and from places and arrival time using the internet via cell phone to the driver based on GIS and GPS. However, even with a good navigation system, it losses the shortest route when there is an average speed of the vehicle being between S-15 kilometers. Therefore, in order to improve the vehicle waiting time and average vehicle speed, we are suggesting an optimal green time algorithm using fuzzy adaptive control, where there are different traffic intersection lengths, and lanes. In this paper, to be able to assist the driver and forecast the optimal traffic information with regards to the road conditions; dangerous roads, construction work and estimation of arrival time at their destination using internet.

• Journal of the Society of Naval Architects of Korea
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• v.58 no.5
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• pp.303-313
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• 2021

Recently, quality control of the Liquefied Natural Gas Carrier (LNGC) cargo hold and block-erection interference areas using 3D scanners have been performed, focusing on large shipyards and the international association of classification societies. In this study, as a part of the research on LNGC cargo hold quality management advancement, a study on deep-learning-based scaffolding system 3D point cloud object detection and post-processing were conducted using a LNGC cargo hold 3D point cloud. The scaffolding system point cloud object detection is based on the PointNet deep learning architecture that detects objects using point clouds, achieving 70% prediction accuracy. In addition, the possibility of improving the accuracy of object detection through parameter adjustment is confirmed, and the standard of Intersection over Union (IoU), an index for determining whether the object is the same, is achieved. To avoid the manual post-processing work, the object detection architecture allows automatic task performance and can achieve stable prediction accuracy through supplementation and improvement of learning data. In the future, an improved study will be conducted on not only the flat surface of the LNGC cargo hold but also complex systems such as curved surfaces, and the results are expected to be applicable in process progress automation rate monitoring and ship quality control.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.70-80
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• 2015

In recent years, tram has been the focus of a new mode of public transportation that can solve traffic jams and decrease public transit usage and environmental problem. This research is in the works to develop a tram signal controller and signal control strategies, and aim to resolve the problem of what could happen if a tram system was installed in general road. We developed the hierarchical signal control strategies to obtain a minimum tram bandwidth and to minimize vehicle delay, in order to perform a priority control to include passive and active signal priority control strategies. The strategies was produced for S/W and H/W, it is based in standard traffic signal controller. We conducted a micro simulation test to evaluate the hierarchical signal control strategies, which showed that the developed optimization model is effective to prevent a tram's stop in intersection, to reduce a tram's travel time and vehicle's delay.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.5
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• pp.57-70
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• 2009

According to the change of the traffic conditions, the requirement of controlling the separated left(or right) turn, the median bus lane and bicycle signal is increasing. However, the traffic signal controller standard based on the four-set lights restricts to control the three-set lights which control the separated direction and kind of traffics. This study suggests the method to control the three-set lights signal by improving the hardware and software for the traffic signal controller which is operated currently in the traffic scene. The 6 output ports of Load Signal Unit(LSU) which is consisted of Pedestrian Red, Pedestrian Green, Red, Yellow, Arrow and Green signal reconstitute 2 rows of the Red, Yellow, Green for three-set lights while the Signal Map data's code values which control the signal step of an individual Ring and LSU are established to adjust the LSU's output ports(R1 Y1 G1 R2 Y2 G2) of the three-set lights. The effect of using the separated through/left turn and the median lane bus signal of three-set lights is analyzed from a Mangwoo intersection in Seoul. The results of analysis show that the delay time of the east-west direction where the median bus lane is operated is especially improved with over 70 sec/veh.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.161-167
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• 2004

While most or fixed-time control systems such as UTCS produce the signal timing plans that either maximizing bandwidth or minimizing a disutility index of delay and stops, cannot consider the fluctuation of traffic flow. One category of the traffic-response control systems, which make small changes on a predefined signal plan such as SCOOT, cannot be easily modified for feedback real-time control schemes based on observation of variables other than traffic flow. The other category, which decide to whether switch the traffic lights or not at each step of time as in PRODYN, does not adequately consider the relations between traffic flows and traffic lights at each step of time. In this paper we present a complete formulation that adequately consider the relations between traffic flows and traffic lights at each step of time. The formulation is a binary mixed integer linear programing (BMILP) that obtain traffic lights at each step for minimizing delay. Since numarical examples for application of the proposed model illustrated that the model adequately produced dynamic traffic signal plans minimizing delay at each step, the model may be expected to contribute to advanced transportation management systems (ATMS) for dynamic traffic signal control.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.54-62
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• 2018

As a part of realization of artificial intelligence signal(AI Signal), this study proposed an actuated signal algorithm based on vehicle queue length that estimates in real time by deep learning. In order to implement the algorithm, we built an API(COM Interface) to control the micro traffic simulator Vissim in the tensorflow that implements the deep learning model. In Vissim, when the link travel time and the traffic volume collected by signal cycle are transferred to the tensorflow, the vehicle queue length is estimated by the deep learning model. The signal time is calculated based on the vehicle queue length, and the simulation is performed by adjusting the signaling inside Vissim. The algorithm developed in this study is analyzed that the vehicle delay is reduced by about 5% compared to the current TOD mode. It is applied to only one intersection in the network and its effect is limited. Future study is proposed to expand the space such as corridor control or network control using this algorithm.