• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1553-1559
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• 2017

This paper proposes a lane departure detection algorithm using a single camera equipped in front of a vehicle. The proposed algorithm generates a partial top-view image for a small ROI (region of interest) designated on the top-view space form the image acquired by the camera, detects lanes on the small partial top-view image, and makes a decision on the lane departure by checking overlap between the pre-assigned virtual vehicle and the detected lanes. The proposed algorithm also includes the removal of lines occurred by road symbols (noises) disturbing the lane departure detection between lanes and the prediction of lost lanes using lane information of previous fames. In lane departure detection test using real road videos, the proposed algorithm makes the right decision of 99.0% in lane keeping conditions and 94.7% in lane departure conditions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.13-21
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• 2015

This study focuses on operational analysis of 2 types of intersection shared lanes. First, the analysis showed that a through & right-turn shared lane is always less used than the adjacent through-only lanes and as a result, operational efficiency deteriorates. To improve the efficiency fine-tuning in signal timing optimization using lane-by-lane traffic volume data is required. Further improvement can be achieved by guiding drivers to equally use the shared lane. For left-turn & U-turn shared lanes, it was found that saturation flow rate is affected by interference between U-turn and conflicting right-turn movements. However, since such interference does not occur in every cycle, a statistical model must be established to develop realistic adjustment factor for saturation flow rate of the shared lane.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.339-346
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• 2008

The research was conducted to investigate the characteristics of lateral wheel path distributions (wandering) in different traffic lanes. The lateral wheel path distributions may affect pavement life and various distress types. The results presented that the normal distribution curve with symmetry was observed in the 2-lane and 3-lane roads. In the case of the 2-lane road (on one direction), the wanderings were 70-95cm, and 70-85cm for the 1st and 2nd lanes, respectively, while in the case of the 3-lane road (on one direction), 50-60cm, 65-85cm, and 80-95cm for the 1st, 2nd, and 3rd lanes, respectively. In addition, the 1st lane vehicles tended to pass on the right side to avoid the opposite side vehicles, while the outside lane vehicles tended to pass on the left side to avoid the walkway.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.130-136
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• 2015

In this paper, we propose a robust curved lane marking detection method. Several lane detection methods have been proposed, however most of them have considered only straight lanes. Compared to the number of straight lane detection researches, less number of curved-lane detection researches has been investigated. This paper proposes a new curved lane detection and tracking method which is robust to various illumination conditions. First, the proposed methods detect straight lanes using a robust road feature image. Using the geometric relation between a vehicle camera and the road plane, several circle models are generated, which are later projected as curved lane models on the camera images. On the top of the detected straight lanes, the curved lane models are superimposed to match with the road feature image. Then, each curve model is voted based on the distribution of road features. Finally, the curve model with highest votes is selected as the true curve model. The performance and efficiency of the proposed algorithm are shown in experimental results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.11
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• pp.1879-1886
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• 2016

In this paper, we propose a real-time recognition algorithm of lanes, stop lines and speed bumps on roads for autonomous vehicles. First, we generate a top-view using the image transmitted from a camera that is installed to see the front of a vehicle. To speed up the processing, we simplify the mapping algorithm in constructing a top-view wherein the region of interest (ROI) is concerned. The features of lanes, stop lines and speed bumps, which are composed of lines, are searched in the edge image of the top-view, then followed by labeling and clustering specialized to detect straight lines. The width of lines, distances from the center of a vehicle, and curvature of each cluster are considered to select final candidates. We verify the proposed algorithm on real roads using the commercial car (KIA K7) which is converted into an autonomous vehicle.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.169-176
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• 2005

This paper introduces the dynamic control of acceleration lanes at freeway-ramp junctions. The feasibility of operation with flexible length of acceleration lane was tested with most possible traffic conditions. The operational qualify was also evaluated using average speed and total thru-put at both ramp section and freeway section. A CORSIM microscopic simulation model was used to evaluate the operation quality with a variety or volume conditions and three acceleration lanes, each representing different length categories. In addition, tollgate O-D data including travel times were obtained for two sections on the Gyeong-bu Freeway where an effective merging distance has been largely reduced. Its effect was analyzed and compared to the simulation results. Finally, the effects of acceleration lane are discussed and operational improvement at junctions is presented as research findings.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.19-26
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• 2012

Reversible lanes in urban intersections is used to efficiently control vehicles, reduce traffic congestion and increase the capacity of a roadway. But by far traffic control systems in urban intersections are simple and manually operated by police officers. In this study, we present a hybrid algorithm that intelligently resolve the moving direction of reversible lanes to efficiently manage the flow of traffic at intersection. The proposed algorithm consists of three stages:(i) fuzzy inference method to get the efficiency of moving direction, (ii) a provisional decision whether to change the reversible lane to different direction, (iii) a final evaluation criterion for changing the directions of the reversible lanes. The fuzzy inference results of efficiency are shown by using matlab application.

• International Journal of Highway Engineering
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• v.16 no.4
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• pp.119-126
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• 2014

PURPOSES: Used in transportation planning and traffic engineering, almost traffic simulation tools have input variable values optimized by overseas traffic flow attribution because they are almost developed in overseas country. Thus, model calibration appropriated for internal traffic flow attribution is needed to improve reliability of simulation method. METHODS : In this study, the traffic flow model calibration is based on expressways. For model calibration, it needs to define each expressway link according to attribution, thus it is classified by design speed, geometric conditions and number of lanes. And modified greenshield model is used as traffic flow model. RESULTS : The result of the traffic model calibration indicates that internal congested density is lower than overseas. And the result of analysis according to the link attribution indicates that the more design speed and number of lanes increase, the lower the minimum speed, the higher the congested density. CONCLUSIONS: In the traffic simulation tool developed in overseas, the traffic flow is different as design speed and number of lanes, but road segment don't affect traffic flow. Therefore, these results need to apply reasonably to internal traffic simulation method.

• Journal of Korea Multimedia Society
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• v.15 no.8
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• pp.996-1003
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• 2012

We present a nearby vehicle detection method in the adjacent lane using in-vehicle front view camera. Nearby vehicles in adjacent lanes show various appearances according to their relative positions to the host vehicle. Therefore, most conventional methods use motion information for detecting nearby vehicles in adjacent lanes. However, these methods can only detect overtaking vehicles which have faster speed than the host vehicle. To solve this problem, we use the feature of regions where nearby vehicle can appear. Consequently, our method cannot only detect nearby overtaking vehicles but also stationary and same speed vehicles in adjacent lanes. In our experiment, we validated our method through various whether, road conditions and real-time implementation.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.1-7
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• 2016

ADAS (Advanced Driver Assistance Systems) requires not only real-time robust lane detection, both straight and curved, but also predicting upcoming steering direction by detecting the curvature of lanes. In this paper, a curvature lane detection algorithm is proposed to enhance the accuracy and detection rate based on using inverse perspective images and Gaussian Mixture Model (GMM) to segment the lanes from the background under various illumination condition. To increase the speed and accuracy of the lane detection, this paper used template matching, RANSAC and proposed post processing method. Through experiments, it is validated that the proposed algorithm can detect both straight and curved lanes as well as predicting the upcoming direction with 92.95% of detection accuracy and 50fps speed.