• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.121-129
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• 2015

This paper presents a multiple vehicle recognition algorithm based on radar and vision sensor fusion for lane change assistance. To determine whether the lane change is possible, it is necessary to recognize not only a primary vehicle which is located in-lane, but also other adjacent vehicles in the left and/or right lanes. With the given sensor configuration, two challenging problems are considered. One is that the guardrail detected by the front radar might be recognized as a left or right vehicle due to its genetic characteristics. This problem can be solved by a guardrail recognition algorithm based on motion and shape attributes. The other problem is that the recognition of rear vehicles in the left or right lanes might be wrong, especially on curved roads due to the low accuracy of the lateral position measured by rear radars, as well as due to a lack of knowledge of road curvature in the backward direction. In order to solve this problem, it is proposed that the road curvature measured by the front vision sensor is used to derive the road curvature toward the rear direction. Finally, the proposed algorithm for multiple vehicle recognition is validated via field test data on real roads.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.151-160
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• 2010

For the realization of future intelligent transportation systems, fine-grained lane-by-lane traffic monitoring and control functionalities are among the most important technology barriers to overcome. To satisfy the accuracy requirement for traffic monitoring, a GNSS receiver network is designed. The designed receiver network consists of three different types of entities; reference server, broadcaster, and client. For deployment flexibility, all the entities utilize the international message standard RTCM SC-104 version 3.0. For fine-grained traffic monitoring, the client is designed to utilize position-domain carrier-smoothed-code filters to provide accurate vehicle coordinates in spite of frequent addages and outages of visible satellites. An experiment result is presented to evaluate the positioning accuracy of the proposed method.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.29-39
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• 2000

Position of stop line according to left turn trajectory at intersections was studied. The Purpose of this study is to suggest a design guideline of left turn trajectory at intersections which is related to the Position of cross road stop line. Distance from the curb line to the stop line at each lane was calculated and discussed for various combination of road widths. Three design vehicle type and three control radii were considered. Setbacks of stop line from the curb line are Proportional to the control radius which depends on type of design vehicle. 8m, lim and 19m setback for control radius of 12m, 15m and 23m were calculated respectively as their maximum value. This result will be helpful to Paint the road marking on the Pavement which is usually difficult to fit to the designated radius. Field study of the effect of left turn trajectory on flow rate and safety was conducted. It was approved that improperly designed left turn trajectory decreases left turn capacity and increases conflicts among left turn flows of the adjacent lane.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.591-601
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• 2018

This paper discusses methods to effectively operates and evaluates an infrastructure system for lane-level positioning based on satellite navigation. The lane-level positioning infrastructure provides correction information on range measurements with integrity information on the correction to a user with a single frequency (cheap) satellite navigation receiver in order to perform lane-level positioning and integrity monitoring on the position estimate. The architecture and configuration of the lane-level positioning system are described from the systematic level in order to provide a comprehensive insight of the system. The operation/evaluation system for the integrated infrastructure is then presented. The evaluation results of the real implemented system are provided. Based on the results, we discuss requirements to increase the system stability from the operation perspective.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1375-1378
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• 1997

In this paper, we presents the algorithm which is to recognize the traffic sign on the road the traffic signal in a video image for autonomous navigation. First, the rocognition of traffic sign on the road can be detected using boundary point estimation form some scan-lines within the lane deducted. For this algorithm, index matrix method is used to detemine what sign is. Then, the traffic signal recognition is performed by usign the window minified by several scan-lines which position may be expected. For this algoritm, line profile concept is adopted.

• Journal of Korean Society of Transportation
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• v.10 no.2
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• pp.5-24
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• 1992

This research presets the method of determining basic capacity of signalized intersection using the concept of ideal saturation flow rate. Vehicle discharge rates during green time were collected and studied as part of the preparation of Korean Highway Capacity Manual. From the result of this study the ideal saturation flow rate and saturation queue position were determined. In addition, based on the ideal saturation flow rate two geometric adjustment factors(lane width and grade adjustment factors) were studied. The results were presented in this paper.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1802-1803
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• 2011

The Korea Railroad Research Institute (KRRI) is developing the Bimodal-tram. The vehicle has a navigation control system (NCS) for automatic driving. The vehicle has to follow a reference path in automatic mode. NCS uses magnetic markers to calculate the vehicle position. The vehicle lane is marked with permanent magnets that are buried in the road. In this purpose, we show the characteristics and the configuration of NCS.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.383-387
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• 1996

This paper presents a steering control strategy applicable to vehicle path following problems. This control strategy is based on realistic nonlinear equations of motion of multibody systems described in terms of relative joint coordinates. The acceleration of the steering angle is selected as a control input of the system. This input is obtained by considering position and slope errors at current and at advance times. This steering control strategy is tested in circular and lane change maneuvers with a nonlinear vehicle model.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.496-500
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• 1998

Not merely running at the designated constant speed as the classical cruise control, the adaptive cruise control (ACC) maintains safe headway distance when the front is blocked by other vehicles. One of the most essential part of ACC System is the range sensor which can measure the position and speed of all objects in front continuously, ignore all irrelevant objects, distinguish vehicles in different lanes and lock on to the closest vehicle in the same lane. In this paper, the hierarchical object recognition algorithm (HORA) is proposed to process raw scanning laser data and acquire valid distance to target vehicle. HORA contains two principal concepts. First, the concept of life quantifies the reliability of range data to filter off the spurious detection and preserve the missing target position. Second, the concept of conformation checks the mobility of each obstacle and tracks the position shift. To estimate and predict the vehicle position Kalman filter is used. Repeatedly updated covariance matrix determines the bound of valid data. The algorithm is emulated on computer and tested on-line with our ACC vehicle.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.1046-1052
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• 2016

For the safe driving of autonomous vehicles, accurate position estimation is required. Generally, position error must be less than 1m because of lane keeping. However, GPS positioning error is more than 1m. Therefore, we must correct this error and a map matching algorithm is generally used. Especially, road marking intensity map have been used in many studies. In previous work, 3D LIDAR with many vertical layers was used to generate a local intensity map. Because it can be obtained sufficient longitudinal information for map matching. However, it is expensive and sufficient road marking information cannot be obtained in rush hour situations. In this paper, we propose a localization algorithm using an accumulated intensity local map. An accumulated intensity local map can be generated with sufficient longitudinal information using 3D LIDAR with a few vertical layers. Using this algorithm, we can also obtain sufficient intensity information in rush hour situations. Thus, it is possible to increase the reliability of the map matching and get accurate position estimation result. In the experimental result, the lateral RMS position error is about 0.12m and the longitudinal RMS error is about 0.19m.