• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.21-30
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• 2005

In this paper, we propose lane detection and trackinB algerian using B-Snake as robust algorithm. One of chief virtues of Lane detection algorithm using B-Snake is that it is possible to specify a wider range of lane structure because B-Spline conform an arbitrary shape by control point set and that it doesn't use any camera parameter. Using a robust algorithm called CHVEP, we find the vanishing point, width of lane and mid-line of lane because of the perspective parallel line and then we can detect the both side of lane mark using B-snake. To demonstrate that this algorithm is robust against noise, shadow and illumination variations in road image, we tested this algorithm about various image divided by weather-fine, rainy and cloudy day. The percentage of correct lane detection is over 95$\%$.

• International Journal of Highway Engineering
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• v.17 no.5
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• pp.47-56
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• 2015

PURPOSES: The purpose of this study is to estimate the impact of variable message signage (VMS) on traffic safety as a function of road curve radius using statistical methods. METHODS: In order to analyze the impact of VMS installations on traffic safety, travel speed, lateral distance, and geometric data relating to road curvature in each study area was acquired and analyzed for the impact of providing VMS information on driver performance and traffic safety using statistical methods including student t-test, Mann-Whitney test, and the Anderson-Darling test for estimating traffic safety hazard zone in each lane. RESULTS: As a result of analyzing driver performance characteristics before and after providing VMS information, it was determined that by providing VMS information, mean travel speed is deceased and vehicles are driven with increased precision, following the centerline in the first and second lanes. Also the results of analyzing traffic safety impacts of VMS indicate that traffic safety performance factors in the first lane of the Gapyeong section can, on average, increase in the left and right side of the lane by 19.22% and 68.98%, respectively, and in the case of the second lane, safety impacts, on average, can increase in both sides by 100%. For the Hongcheon section, traffic safety impacts in the first lane, on average, can increase along the left and right sides of the lane by 32.31% and 47.18%, and within the second lane, traffic safety can be increased along the left and right side of the lane by 10.97% and -0.01%, respectively. CONCLUSIONS: Based on the results of this study, the impact on traffic safety obtained by providing VMS information for road sections with smaller curve radii is greater than can be obtained for road sections with larger curve radii.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.6
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• pp.413-422
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• 2013

In this paper, we propose a novel method for real-time lane detection that is robust for inclined roads and not require a camera parameter, the Inverse Perspective Transform of the image, and the proposed lane filter. After finding the vanishing point from the start frame of the image and storing the region surrounding the vanishing point as the Template Area(TA), our method predict the lanes by scanning toward the lower part from the vanishing point of the image and obtain the image removed the perspective effect using the Inverse Perspective Transform coefficients extracted based on the predicted lanes. To robustly determine lanes on inclined roads, the region surrounding the vanishing point is set up as the template area (TA), and, by recalculating the vanishing point by tracing the area similar to the TA (SA) in the input image through template matching, it responds to the changes on the road conditions. The proposed method for a more robust lane detection method for inclined roads is a lane detection method by applying a lane detection filter on an image removed of the perspective effect. Through this method, the processing region is reduced and the processing procedure is simplified to produce a satisfactory lane detection result of about 40 frames per second.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.182-188
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• 2011

This paper describes a method of road tracking by using a vision and laser with extracting road boundary (road lane and curb) for navigation of intelligent transport robot in structured road environments. Road boundary information plays a major role in developing such intelligent robot. For global navigation, we use a global positioning system achieved by means of a global planner and local navigation accomplished with recognizing road lane and curb which is road boundary on the road and estimating the location of lane and curb from the current robot with EKF(Extended Kalman Filter) algorithm in the road assumed that it has prior information. The complete system has been tested on the electronic vehicles which is equipped with cameras, lasers, GPS. Experimental results are presented to demonstrate the effectiveness of the combined laser and vision system by our approach for detecting the curb of road and lane boundary detection.

• 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.

• Journal of Auto-vehicle Safety Association
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• v.6 no.2
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• pp.29-35
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• 2014

Lane Keeping Assistance System(LKAS) is a kind of Advanced Driver Assistance Systems(ADAS) which are developed to automate/ adapt/ enhance vehicle systems for safety and better driving. The main system function of LKAS is to support the driver in keeping the vehicle within the current lane. LKAS acquires information on the position of the vehicle within the lane and, when required, sends commands to actuators to influence the lateral movement of the vehicle. Recently, the vehicles equipped with LKAS are commercially available in a few vehicle-advanced countries and the installation of LKAS increases for safety enhancement. The test procedures for LKAS evaluations are being discussed and developed in international committees such as ISO(the International Organization for Standardization). In Korea, the evaluations of LKAS for vehicle safety are planned to be introduced in 2016 KNCAP(Korean New Car Assessment Program). Therefore, the test procedures of LKAS suitable for domestic road and traffic conditions, which accommodate international standards, should be developed. In this paper, some bullet points of the test procedures for LKAS are discussed by extensive researches of previous documents and reports, which are released in public in regard to lateral test procedures including LKAS and Lane Departure Warning System(LDWS). Later, it can be helpful to make a draft considering domestic traffic situations for test procedures of LKAS.

• ETRI Journal
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• v.44 no.4
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• pp.641-653
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• 2022

In the process of autonomous vehicle motion planning and to create comfort for vehicle occupants, factors that must be considered are the vehicle's safety features and the road's slipperiness and smoothness. In this paper, we build a mathematical model based on the combination of a genetic algorithm and a neural network to offer lane-change solutions of autonomous vehicles, focusing on human vehicle control skills. Traditional moving planning methods often use vehicle kinematic and dynamic constraints when creating lane-change trajectories for autonomous vehicles. When comparing this generated trajectory with a man-generated moving trajectory, however, there is in fact a significant difference. Therefore, to draw the optimal factors from the actual driver's lane-change operations, the solution in this paper builds the training data set for the moving planning process with lane change operation by humans with optimal elements. The simulation results are performed in a MATLAB simulation environment to demonstrate that the proposed solution operates effectively with optimal points such as operator maneuvers and improved comfort for passengers as well as creating a smooth and slippery lane-change trajectory.

• Journal of Korean Society of Transportation
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• v.1 no.1
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• pp.56-63
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• 1983

Intersection control has dual-purposes; increasing capacity and reducing delay. The primary concern of efficient intersection control under oversaturated condition as in Korea is to increase capacity. Prevailing intersection operation technique permits thru traffic to utilize left turn lane, because the intersection without left turn pocket has left turn signal interval. In this situation, it seems not to be valid to calculate capacity, delay, and signal timings by conventional methods. By critical lane technique, capacity increases as cycle length increases. However, when thru traffic utilize LT lane, the capacity varies according to LT volume, LT interval as well as cycle length, which implies that specific cycle length and LT interval exist to maximize capacity for given LT volume. The study is designed is designed to calculate utilization factors of LT lane for thru traffic and capacities, and identify signal timings to yield maximum capacity. The experimental design involved has 3 variables; 1)LT volumes at each approach(20-300 vph), 2)cycle lengths (60-220 sec), and 3)LT intervals(2.6-42 sec) for one scenario of isolated intersection crossing two 6-lanes streets. For LT volume of 50-150 vph, capacity calculated by using the utilization factor is about 25% higher than that by critical lane method. The range of optimum cycle length to yield maximum capapcity for LT volume less than 120 vph is 140-180 sec, and increases as LT volume increases. The optimum LT interval to yield maximum capacity is longer than the intrval necessary to accommodate LT volume at saturation flow rate.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.23-31
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• 2002

The headway of vehicles entering an intersection is closely related with the saturation flow rate and is a basic parameter required for determining the saturation headway and the start-up lost delay. Since such headway value reflects the drivers' behaviors and features of the intersection, all intersections don't have an equal value, but are affected by number and location of their lanes, changing types, local characteristics and time zone. Accordingly, this study attempted to suggest proper values on the basis of data by investigating headway in lanes. Number of exclusive through lanes was divided into single lane, double lanes and triple lanes, the locations of lanes were divided into inside lane, central lane and outside lane. As a result of investigating the headway, single through lane, double through lanes-inside lane, and triple through lane-outside lane showed as 1.73 sec., 1.71 sec. and 1.93sec., respectively. The result of calculating the area factor of business areas by fixing 1.00 for the residental area and applying relation between headway and saturation flow rate was 0.96. In the case of start-up lost delay lead dual left turn and directional separation were 1.41 sec. and 3.27 sec., respectively, showing the great difference. Therefore, different start-up lost delay according to changing type should be applied.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.3
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• pp.139-147
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• 2007

In military transportation, the use of wide trailer for transporting the large and heavy weight equipments such as tank, armoured vehicle, and mobile gunnery is quite common. So, the vulnerability of causing traffic accidents for these wide military trailer to bump or collide with another car in adjacent lane is very high due to its broad width in excess of its own lane's width. Also, the possibility of these strayed accidents can be increased especially by the careless driver. In this paper, the recognition system of lane and vehicle headway direction is developed to detect the possible collision and warn the driver to prevent the fatal accident. In the system development, Kalman filtering is used first to extract the border of driving lane from the video images supplied by the CCD camera attached to the vehicle and the driving lane detection is completed with regression analysis. Next, the vehicle headway direction is recognized by using neural network scheme with the extracted parameters of the detected driving lane feature. The practical experiments for the developed system are also carried out in the real traffic road of Seoul city area and the results show us the more than 90% accuracy in recognizing the driving lane and vehicle headway direction.