• 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 Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.158-164
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• 2015

Lane detection is one of the key parts among autonomous vehicle technologies because lane keeping and path planning are based on lane detection. Camera is used for lane detection but there are severe limitations such as narrow field of view and effect of illumination. On the other hands, Lidar sensor has the merits of having large field of view and being little influenced by illumination because it uses intensity information. Existing researches that use methods such as Hough transform, histogram hardly handle multiple lanes in the co-occuring situation of lanes and road marking. In this paper, we propose a method based on RANSAC and regularization which provides a stable and precise detection result in the co-occuring situation of lanes and road marking in highway scenarios. This is performed by precise lane point extraction using circular model RANSAC and regularization aided least square fitting. Through quantitative evaluation, we verify that the proposed algorithm is capable of multi lane detection with high accuracy in real-time on our own acquired road data.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.357-360
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• 2013

A 1.8V 2-Gb/s scalable low voltage signaling (SLVS) transmitter (TX) is designed for mobile applications requiring high speed and low power consumption. It consists of 4-lane TX for data transmission, 1-lane TX for a source synchronous clocking, and a 8-phase clock generator. The proposed SLVS TX has the scaling voltage swing from 50 mV to 650 mV and supports a high speed (HS) mode and a low power (LP) mode. An output impedance calibration scheme for the SVLS TX is proposed to improve the signal integrity. The proposed SLVS TX is implemented by using a $0.18-{\mu}m$ 1-poly 6-metal CMOS with a 1.8V supply. The simulated data jitter of the implemented SLVS TX is about 8.04 ps at the data rate of 2-Gbps. The area and power consumption of the 1-lane of the proposed SLVS TX are $422{\times}474{\mu}m^2$ and 5.35 mW/Gb/s, respectively.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.29-39
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• 2019

As mobile robot applications increase in real life, the need of low cost autonomous driving are gradually increasing. We propose a novel vision-based real-time lane detection and tracking system that supports autonomous driving of mobile robots in constrained tracks which are designed considering indoor driving conditions of mobile robots. Considering the processing of lanes with various shapes and the pre-adjustment of operation parameters, the system structure with multi-operation modes are designed. In parameter tuning mode, thresholds of the color filter is dynamically adjusted based on the geometric property of the lane thickness. And in the unstable input mode of curved tracks and the stable input mode of straight tracks, lane feature pixels are adaptively extracted based on the geometric and temporal characteristics of the lanes and the lane model is fitted using the least-squared method. The track centerline is calculated using lane models and the motion model is simplified and tracked by a linear Kalman filter. In the driving experiments, it was confirmed that even in low-performance robot configurations, real-time processing produces the accurate autonomous driving in the constrained track.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2D
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• pp.227-234
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• 2009

At present, the length of deceleration lane at freeway diverging areas are designed based on the design speed of main lines and ramps. This is possible on assumption that diverging vehicles decelerate at deceleration section after moving to shoulder lane in advance. But with high diverging volume, several vehicles will try to change to exit lane at the same time. This will cause the distribution of main lane flows or some vehicles may encounter short deceleration length because they miss the proper time to change the lane. The purpose of this study is to establish a design guideline of the length of deceleration section considering the volume of diverging traffic. Also, the results of analysis by the FRESIM simulation model shows that some improvements in respect of delays, speeds and speed deviations of mainline and deceleration lane.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.110.3-110
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• 2002

$\textbullet$ Lane detection by TFALDA $\textbullet$ SVM for large scale data and multiclass classification problem $\textbullet$ TLC Classification $\textbullet$ Lateral offset estimation by IPT $\textbullet$ Lane departure warning by a fuzzy system $\textbullet$ Experimental results by HiLS $\textbullet$ Conclusion

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.147-152
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• 2003

Aerial Images are usually used to extract 3-D coordinates of various urban features. In this process, the stereo matching of images should be performed precisely to extract these information from aerial Images. In this research, we proposed a matching technique based on geometric features of lanes. We extracted lanes from aerial images and grouped into 4 lane's types. They are lane lines, dotted lines, arrow lane, safety zone. After preprocessing, We will match them by spatial relationships, for example, the distance and orientation between the extracted features. In the future, we will obtain lane coordinates and reconstruct 3-d coordinates of roads.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1416-1418
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• 2004

This paper proposes an image processing algorithm for detecting obstacles on road-lane using DLI(disparity of lane-related information) that is generated by stereo images acquired from dual cameras mounted on a moving vehicle. The DLI is a disparity that is acquired using single lane information from road lane detection. For the purpose to reduce processing time, we use small blocks obtained by edge-histogram based blocking logic. This algorithm detects moving objects such as preceding vehicles and obstacles. The proposed algorithm has been implemented in a personal computer with the road image data of a typical highway. We successfully performed experiments under a wide variety of road conditions without changing parameter values or adding human intervention. Experimental results also showed that the proposed DLI is quite successful.