• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.3
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• pp.230-237
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• 2004

Lane Sensing techniques based on vision sensors are regarded promising because they require little infrastructure on the highway except clear lane markers. However, they require more intelligent processing algorithms in vehicles to generate the previewed roadway from the vision images. In this paper, a lane sensing algorithm using vision sensors is developed to improve the sensing robustness. The parallel stereo-camera is utilized to regenerate the 3-dimensional road geometry. The lane geometry models are derived such that their parameters represent the road curvature, lateral offset and heading angle, respectively. The parameters of the lane geometry models are estimated by the Kalman filter and utilized to reconstruct the lane geometry in the global coordinate. The inverse perspective mapping from the image plane to the global coordinate considers roll and pitch motions of a vehicle so that the mapping error is minimized during acceleration, braking or steering. The proposed sensing system has been built and implemented on a 1/10-scale model car.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.17-31
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• 2003

This study is about throughput analysis of the shared right turn lane at signalized intersection with lane width change. It is expected that the increased width of the right turn shared lane causes to increase the volume of right turn on red(RTOR) In this study, the throughput computation is designed to take into account the lost time which is caused by the blocked right turn due to the stop of through traffic. The saturation flow rate of right turn using the rest of lane after through traffic stops is included as well. Results show that the different RTOR volume levels due to the various shared lane width leads to a difference in throughput. For the shared right turn lanes. throughput capacity for various lane widths is bigger than that of the KHCM as much as from 1.1 to 2.1 times.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.329-336
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• 2006

This paper describes a lane change assistance system for the help of safe lane change, which detects vehicles approaching from the rear side by using a computer vision algorithm and notifies the possibility of safe lane change to a driver. In case a driver tries to lane change, the proposed system can detect vehicles and keep track of them. After detecting side lane lines, region of interest for vehicle detection is decided. For detection a vehicle, optical flow technique is applied. The experimental result of the proposed algorithm and system showed that the vehicle detection rate was 91% and the embedded system would have application to a lane change assistance system being commercialized in the near future.

• Journal of the Semiconductor & Display Technology
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• v.15 no.1
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• pp.27-32
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• 2016

A new lane detection algorithm is proposed for the analysis of DNA fingerprints from a polymerase chain reaction (PCR) gel electrophoresis image. Although several research results have been previously reported, it is still challenging to extract lanes precisely from images having abrupt background brightness difference and bent lanes. We propose an edge based algorithm for calculating the average lane width and lane cycle. Our method adopts sub-pixel algorithm for extracting rising-edges and falling edges precisely and estimates the lane width and cycle by using k-means clustering algorithm. To handle the curved lanes, we partition the gel image into small portions, and track the lane centers in each partitioned image. 32 gel images including 534 lanes are used to evaluate the performance of our method. Experimental results show that our method is robust to images having background difference and bent lanes without any preprocessing.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1396-1406
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• 2018

Lane detection is a key function in developing autonomous vehicle technology. In this paper, we propose a lane marker detection algorithm robust to environmental variation targeting low cost embedded computing devices. The proposed algorithm consists of two phases: initialization phase which is slow but has relatively higher accuracy; and the tracking phase which is fast and has the reliable performance in a limited condition. The initialization phase detects lane markers using a set of filters utilizing the various features of lane markers. The tracking phase uses Kalman filter to accelerate the lane marker detection processing. In a tracking phase, we measure the reliability of the detection results and switch it to initialization phase if the confidence level becomes below a threshold. By combining the initialization and tracking phases we achieved high accuracy and acceptable computing speed even under a low cost computing resources in which we cannot use the computing intensive algorithm such as deep learning approach. Experimental results show that the detection accuracy is about 95% on average and the processing speed is about 20 frames per second with Raspberry Pi 3 which is low cost device.

• 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.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.1069-1079
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• 2012

Lane detection with the use of a camera is an essential task required for the development of advanced driving assistance system. In this paper, edges of the lane are generated by applying Canny's method. The edge detection usually makes different results for several environmental conditions depending on the clearness of lane quality, so that it sometimes causes wrong lane detection. Therefore, we propose robust algorithm to environmental changes that automatically adjusts parameter for edge detection and generates edges more stably. Based on the acquired edges, we finally generate the spline curve of lane by using Catmull Rom spline.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2814-2818
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• 2000

This paper describes an image processing algorithm capable of recognizing the road lane using a CDF (Cumulative Distribution Function). which is designed for the model function of the road lane. The CDF has distinctive peak points at the vicinity of the lane direction because of the directional and positional continuities of the lane. We construct a scatter diagram by collecting the edge pixels with the direction corresponding to the peak point of the CDF and carry out the principal axis-based line fitting for the scatter diagram to obtain the lane information. As noises play the role of making a lot of similar features to the lane appear and disappear in the image we introduce a recursive estimator of the function to reduce the noise effect and a scene understanding index (SUI) formulated by statistical parameters of the CDF to prevent a false alarm or miss detection. The proposed algorithm has been implemented in a real time on the video data obtained from a test vehicle driven in a typical highway.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.109-118
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• 2009

The conventional lane changing model has been developed without acceleration or deceleration of vehicles at target lane. Thus, existing lane changing models have limitation to apply in real world. In this paper, lane changing model considered acceleration or deceleration, and calculated the safety distance between subject vehicle and adjacent vehicles for lane changing as well. Simulation was conducted to verify the validity and the efficiency of the developed lane changing model in this paper. Several scenarios were carefully examined by safety distance between subject vehicle and adjacent vehicles. In the result, it was verified that if gap between subject vehicle and adjacent vehicles is larger than safety distance, lane changing behavior between subject vehicle and adjacent vehicles avoids collision. The suggested lane changing model may be applied at the future driver assistance system and advanced safety vehicle.

• 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.