• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.115-126
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• 2009

The lane-change behavior usually consists of discretionary lane-change and mandatory lane-change types. For the first type, drivers change lanes selectively to maintain their own driving condition and the second type is the case that the drivers must change the current lane, which can occur in recurrent congestion sections like merging and weaving sections. The mandatory lane-change behavior have a great effect on the operation condition of freeway. In this paper, we first generate data such as traffic volumes, speeds, densities, and the number of lane-change within the merging and weaving sections using the data of individual vehicle collected from time-lapse aerial photography. And then, the data is divided into the stable and congested flow by analyzing the speed variation pattern of individual vehicles. In addition, the number of lane-changing from ramp to mainline within every 30-meter interval is investigated before and after traffic congestion at study sites and the distribution of lane-changing at each 30-meter point is analyzed to identify the variation of lane-changing ratio depending on the stable and congested flows. To recognize the effect of mainline flow influenced by ramp flow, this study also analyzes the characteristics of the lane-changing distributions within the lanes of mainline. The purpose of this paper is to present the basic theory to be used in developing a lane-changing model at the merging and weaving sections on freeways.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.3
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• pp.9-23
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• 2015

A lane change maneuver which has a high driver cognitive workload and skills sometimes leads to severe traffic accidents. In this study, the Advanced Lane Change Assist System (ALCAS) was developed to assist with the automatic lane changes in merging sections which is mainly based on an automatic control algorithm for detecting an available gap, determining the Optimal Lane Change Start Point (OLCSP) in various traffic conditions, and positioning the merging vehicle at the OLCSP safely by longitudinal automatic controlling. The analysis of lane change behavior and modeling of fundamental lane change feature were performed for determining the default parameters and the boundary conditions of the algorithm. The algorithm was composed of six steps with closed-loop. In order to confirm the algorithm performance, numerical scenario tests were performed in various surrounding vehicles conditions. Moreover, feasibility of the developed system was verified in microscopic traffic simulation(VISSIM 5.3 version). The results showed that merging vehicles using the system had a tendency to find the OLCSP readily and precisely, so improved merging performance was observed when the system was applied. The system is also effective even during increases in vehicle volume of the mainline.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.2
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• pp.85-94
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• 2016

Lane Designation is defined as reasonable road management to ensure the road safety and enhance road efficiency. While the lane designation system was abolished in 1999, it was redefined because of the increasing number of large vehicles in the passing lane, violent on driving and traffic accidents in 2000. The needs of improvement on operating the lane designation has been increasing more in recent due to the low ratio of compliance with the system and difficulties to keep the right lane due to need of turning and demand of widening of designates lane for two-wheeled vehicles and truck. In this study, we presented the improvement plan through the question survey, simulation analysis, safety evaluation. It found a problem that the low-speed vehicle is to use the upper level roadway, difficulties of supervision, the imbalance in the lane use, imbalance traffic and does not match the international standards. This study suggested five different alternatives through the survey. micro simulation has used in order to examine each alternative by management effectiveness and feasibility. It analyzed the traffic speed, efficiency, traffic balance of alternatives. Also, safety evaluation conducted in terms of the range of field-of-view to ensure the easiness of field of view by various configurational difference between the vehicles. By the analysis results of such indicators, This study presents proposals for improvement in operating designated lane that low-speed-big-sized vehicles keep to the right lane, and high-speed-small sized vehicles keep to the left lane.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.186-201
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• 2021

As autonomous driving technology advances, the accuracy of the vehicle position is important for recognizing the environments around driving. Map-matching localization techniques based on high definition (HD) maps have been studied to improve localization accuracy. Because conventional map-matching techniques estimate the vehicle position based on an HD map reference dataset representing the center of the lane, the estimated position does not reflect the deviation of the lateral distance within the lane. Therefore, this paper proposes a localization system based on the reference lateral position dataset extracted using image processing and HD maps. Image processing extracts the driving lane number using inverse perspective mapping, multi-lane detection, and yellow central lane detection. The lane departure method estimates the lateral distance within the lane. To collect the lateral position reference dataset, this approach involves two processes: (i) the link and lane node is extracted based on the lane number obtained from image processing and position from GNSS/INS, and (ii) the lateral position is matched with the extracted link and lane node. Finally, the vehicle position is estimated by matching the GNSS/INS local trajectory and the reference lateral position dataset. The performance of the proposed method was evaluated by experiments carried out on a highway environment. It was confirmed that the proposed method improves accuracy by about 1.0m compared to GNSS / INS, and improves accuracy by about 0.04m~0.21m (7~30%) for each section when compared with the existing lane-level map matching method.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.932-937
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• 2003

In this paper, we will explain about the unmanned vehicle control and modeling for combined obstacle avoidance and lane tracking. First, obstacle avoidance is considered as one of the important technologies in the unmanned vehicle. It is consisted by two parts: the first part includes the longitudinal control system for the acceleration and deceleration and the second part is the lateral control system for the steering control. Each system uses to the obstacle avoidance during the vehicle moving. Therefore, we propose the method of vehicle control, modeling and obstacle avoidance. Second, we describe a method of lane tracking by means of vision system. It is important in the unmanned vehicle and mobile robot system. In this paper, we deal with lane tracking and image processing method and it is including lane detection method, image processing algorithm and filtering method.

• International Journal of Highway Engineering
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• v.18 no.6
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• pp.11-24
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• 2016

OBJECTIVES : This study aims to review a plan to reduce the shoulder width of a deformed round-trip two-lane highway with low traffic volume. METHODS : Installation of a passing lane on a round-trip two-lane (one-way one-lane) highway, and reduction of a shoulder for a round-trip four-lane highway. RESULTS : It is necessary to establish a design criterion for various highways, because the plan to reduce the lane or shoulder width of a highway with low traffic volume was analyzed to have an economic efficiency of 6.8~7.0%. CONCLUSIONS : It is necessary to seek for a plan to establish a national trunk net early by efficiently using the limited financial resources to cope with the traffic demand elastically.

• Journal of Korean Society of Transportation
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• v.12 no.1
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• pp.117-132
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• 1994

Drivers select approach lane according to various traffic situations as well as their destination. This behavior affects the utilization of lanes and capacity analysis at urban signalized intersections. This paper presents the concept, behavior of lane utilization, and the lane utilization factors which included in the study. Preparation of Korean Highway Capacity Manual (1992). Lane utilization is affected by various traffic and geometric factors which are roadway side friction, median friction, and number of lanes, etc. and it converges to an equal utilization as the degree of saturation (V/C ratio) increase. Lane utilization factor is suggested by the degree of saturation and the number of lanes, and it is presented in this paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.636-639
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• 2003

In this paper, we present a robust method for detecting other vehicles from n forward-looking CCD camera in a moving vehicle. This system uses edge and shape information to detect other vehicles. The algorithm consists of three steps: lane detection, ehicle candidate generation, and vehicle verification. First after detecting a lane from the template matching method, we divide the road into three parts: left lane, front lane, and right lane. Second, we set the region of interest (ROI) using the lane position information and extract a vehicle candidate from the ROI. Third, we use local orientation coding (LOC) edge image of the vehicle candidate as input to a pretrained neural network for vehicle recognition. Experimental results from highway scenes show the robustness and effectiveness of this method.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.1382-1387
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• 2010

A 3D FEM numerical analysis was performed to observe the changes of supporting system of a old 1-lane tunnel when it is enlarged to 2-lane, 3-lane and 4-lane. The standard Type-III supporting pattern was applied to the new tunnel because the ground was assumed as Type-III. The observation was carried out at the middle supporting system of the old 1-lane tunnel alignment. The results shows that the changes of old tunnel supporting system began when the new tunnel was excavated at 2D(D is the equivalent diameter of 1-lane tunnel) behind of the observation place and became very rapid from 1D.

• Journal of Auto-vehicle Safety Association
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• v.10 no.1
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• pp.38-44
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• 2018

This paper presents an analysis on driving safety in lane change situation based on road driving data. Autonomous driving is a global trend in vehicle industry. LKAS technologies are already applied in commercial vehicle and researches about lane change maneuver have been actively studied. In autonomous vehicle, not only safety control issue but also imitating human driving maneuver is important. Driving data analysis in lane change situation has been usually dealt with ego vehicle information such as longitudinal acceleration, yaw rate, and steering angle. For this reason, developing safety index according to surrounding vehicle information based on human driving data is needed. In this research, driving data is collected from perception module using LIDAR, radar and RT-GPS sensors. By analyzing human driving pattern in lane change maneuver, safety index that considers both ego vehicle and surrounding vehicle state by using relative velocity and longitudinal clearance has been designed.