• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제20권5호
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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.

• Proceedings of the KIEE Conference
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2843-2845
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• 2000

A lane detection based on a road model or feature all need correct acquirement of information on the lane in a image, It is inefficient to implement a lane detection algorithm through the full range of a image when being applied to a real road in real time because of the calculating time. This paper defines two searching range of detecting lane in a road, First is searching mode that is searching the lane without any prior information of a road, Second is recognition mode, which is able to reduce the size and change the position of a searching range by predicting the position of a lane through the acquired information in a previous frame. It is allow to extract accurately and efficiently the edge candidates points of a lane as not conducting an unnecessary searching. By means of removing the perspective effect of the edge candidate points which are acquired by using the inverse perspective transformation, we transform the edge candidate information in the Image Coordinate System(ICS) into the plane-view image in the World Coordinate System(WCS). We define linear approximation filter and remove the fault edge candidate points by using it This paper aims to approximate more correctly the lane of an actual road by applying the least-mean square method with the fault-removed edge information for curve fitting.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제29권1D호
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• pp.25-32
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• 2009

Currently, various types of TDM (Transportation Demand Management) policies are being studied and implemented in an attempt to overcome the limitations of supply oriented policies. In this context, this paper addressed issues of effectiveness and possible domestic implementation of the HOT lane. The possible site of implementation selected for this simulation study is part of the Kyung-bu freeway, where a dedicated bus lane is currently being operated. Minimum length of distance required in between interchanges and access points of the HOT lane for vehicles to safely enter and exit the lane, and traffic management policies for effectively managing the weaving traffic trying to enter and exit the HOT lane were presented. A 5.2km section of freeway from Ki-heuing IC to Suwon IC and a 8.3km section from Hak-uei JC to Pan-gyo JC have been selected as possible sites of implementation for the HOT lane, in which congestion occurs regularly due to the high level of travel demand. VISSIM simulation program has been used to analyze the effects of the HOT lane under the assumption that one-lane HOT lane has been put into operation in these sections and that the lane change rate were in between 5% to 30%. The results of each possible scenario have proven that overall travel speed on the general lanes have increased as well by 1.57~2.62km/h after the implementation of the HOT lane. It is meaningful that this study could serve as a basic reference data for possible follow-up studies on the HOT lane as one effective method of TDM policies. Considering that the bus travel rate would continue increase and assuming the improvement in travel speed on general lanes, similar case study can be implemented where gaps between buses on bus lane are available, as a possible alternative of efficient bus lane management policies.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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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.

• Journal of Korean Society of Transportation
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• 제12권1호
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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.

• Journal of Auto-vehicle Safety Association
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• 제10권1호
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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.

• Journal of the Korea Society of Computer and Information
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• 제22권3호
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• pp.27-34
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• 2017

We propose a cascade lane detector that uses biased discriminant analysis (BDA) to work effectively even when there are various external factors on the road. The proposed cascade detector was designed with an existing lane detector and the detection module using BDA. By placing the BDA module in the latter stage of the cascade detector, the erroneously detected results by the existing detector due to sunlight or road fraction were filtered out at the final lane detection results. Experimental results on road images taken under various environmental conditions showed that the proposed method gave more robust lane detection results than conventional methods alone.

• Journal of Institute of Control, Robotics and Systems
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• 제4권6호
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• pp.759-764
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• 1998

We propose a novel algorithm capable of recognizing the road lane by image processing. Considering the fact that the direction and location of road lane are maintained similarly in successive images we formulate a function to represent the property. However, as noises play the role of making a lot of similar patterns appear and disappear in the road image, keeping of robustness in the lane detection has been known a difficult work. To overcome this problem, we introduce the following three ideas: 1) design of a function based on an edge direction and magnitude, 2) construction of a recursive filter to estimate the function recursively for successive images, 3) principal axis-based line fitting. These concepts enhance the adaptability to cope with the random environment of traffic scene and eventually lead to the reliable detection of a road lane.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제15권6호
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• pp.116-126
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• 2016

In this study, lane-wise traffic flow characteristics were analysed on uninterrupted flow using a new notion of "lane-wise travel speed reversal (LTSR)" which is defined as a phenomena that travel speed in the median lane is lower than other lanes. Mathematical formulation was also proposed to calculate the strength of LTSR. The experiment road site is Seoul Outer Ring Expressway (Jayuro-IC~Jangsoo-IC), and travel trajectories for each four lane were collected for weekdays (Mon. through Fri.) during morning peak. Comparing lane-wise travel speeds for entire test road section, no LTSR was observed, meaning that the travel speed in the median lane is the fastest, followed by 2nd, 3rd, and 4th lane as in order. Howerver, the result of microscopic analysis using 100-meter discrete road section based data shows that LTSR occurs many times. Especially the strength of LTSR is higher in congestion area and freeway merge and diverge segment. It is expected that these results could be used as a fundamental data when establishing lane-by-lane traffic operation strategy and developing lane-wise traffic information collection and dissemination technology.

• Journal of the Korean Society for Precision Engineering
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• 제18권3호
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• pp.68-74
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• 2001

A lane detection based on a road model or feature all needs correct acquirement of information on the lane in an image. It is inefficient to implement a lane detection algorithm through the full range of an image when it is applied to a real road in real time because of the calculating time. This paper defines two (other proper terms including"modes") for detecting lanes on a road. First is searching mode that is searching the lane without any prior information of a road. Second is recognition mode, which is able to reduce the size and change the position of a searching range by predicting the position of a lane through the acquired information in a previous frame. It allows to extract accurately and efficiently the edge candidate points of a lane without any unnecessary searching. By means of inverse perspective transform which removes the perspective effect on the edge candidate points, we transform the edge candidate information in the Image Coordinate System(ICS) into the plan-view image in the World Coordinate System(WCS). We define a linear approximation filter and remove faulty edge candidate points by using it. This paper aims at approximating more correctly the lane of an actual road by applying the least-mean square method with the fault-removed edge information for curve fitting.e fitting.