• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1931-1936
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• 2007

Demand forecasting for railroad traffic is fairly important to establish future policy and plan. The future demand of railroad traffic can be predicted by analyzing the demand of air, marine and bus traffic which influence the demand of railroad traffic. In this study, forecasting the demand of railroad traffic is implemented through neural network using the demand of air, marine and bus traffic. Estimate accuracy of the demand of railroad traffic was shown about 84% through neural net model proposed.

• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.113-118
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• 2016

The walking speed of handicapped people generally is slower than that of normal people. So it is difficult for them to cross at crosswalks within the allotted time provided by the traffic light. This problem can be solved by expanding the time of the traffic light. However, if the latency of the traffic light is increased without distinguishing the handicapped among all other pedestrians, the efficiency of traffic signal lights will decrease. In this paper, we propose a smart traffic signal connecting mechanism between the previous pedestrian traffic signal and a pedestrian's device (smartphone). This Smart pedestrian traffic light, through this mechanism, minimizes traffic congestion by providing additional walking time only to the handicapped among pedestrians. This crosswalk traffic light recognizes the handicapped using a technique called Internet of things (IOT). In this paper, we extract the data necessary to build an effective smart crosswalk traffic light mechanism through simulation techniques. We have extracted different kinds of traffic signal times with our virtual simulation environment to verify the efficiency of the smart crosswalk pedestrian traffic light system. This approach can validate the effective delay time of the traffic signal time through a comparison based on number of pedestrians.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.57-71
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• 2009

Due to increasing interest in dispersion of traffic flows through providing traffic information, there has been much research of driver behavior and effectiveness of diversion. In this paper the authors intend to analyze how a diversion was determined and its effects through correlation analysis between diversion rates estimated by actual surveys and the traffic conditions. Through speed-flow analysis, the diversion mechanism was found. When travel speed decreased, detour volume increased. Then when the traffic volume was decreased through an increase of diversion and traffic conditions got better, the detour volume decreased again. In addition, the authors found negative correlation between the diversion rate and travel speed through correlation analysis. It shows that there were various relationships between diversion rates and traffic conditions according to congestion level and direction of traffic. Finally, it is suggested that the regression equation for calculating the diversion rate with the traffic flows, travel speed, and travel time as variables has a coefficient of determination of 38.5%. It means that traffic conditions on expressways take about 40% of driver's decision-making for diversion.

• Journal of Environmental Impact Assessment
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• v.10 no.4
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• pp.297-304
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• 2001

Recently the road traffic noise has appeared as a significant environmental issue because of dramatic increase of vehicles and expansion of newly constructed road. Therefore, this study proposes the method that improves prediction factors and models through analysis of the existing road traffic noise prediction model. Prediction factors can be improved by establishing guideline for diffraction attenuation and applying daily traffic discharge, peak traffic discharge, and average traveling speed through an analysis of level service. Prediction must be made by periods of one or five years during 20 years. Prediction models also can be improved to include better prediction model through setting the database, establishing functional relation between physical properties and noise levels by acoustic analysis, and developing models for road traffic noise prediction in residential areas.

• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.89-118
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• 1996

The development and implementation of a real-time, traffic adaptive control scheme based on fuzzy logic through Video Image Detector systems (VIDs) is presented. Through VIDs based image processing, fuzzy logic can be used for a real-time traffic adaptive signal control scheme. Fuzzy control logic allows linguistic and inexact traffic data to be manipulated as a useful tool in designing signal timing plans. The fuzzy logic has the ability to comprehend linguistic instructions and to generate control strategy based on a priori verbal communication. The implementation of fuzzy logic controller for a traffic network is introduced. Comparisons are made between implementations of the fuzzy logic controller and the actuated controller in an isolated intersection. The results obtained from the application of the fuzzy logic controller are also compared with those corresponding to a pretimed controller for the coordinated intersections. Simulation results from the comparisons indicate the performance of the system is between under the fuzzy logic controller. Integration of the aforementioned schemes into and ATMS framework will lead to real-time adjustment of the traffic control signals, resulting in significant reduction in traffic congestion.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.105-111
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• 2003

This paper is researching the storing of 40 different kinds of conditions. Such as, car speed, delay in starting time and the volume of cars in traffic. Through the use of a central nervous networking system or AI, using 10 different intersecting roads. We will improve the green traffic light. And allow more cars to easily flow through the intersections. Now days, with increasing many vehicles on restricted roads, the conventional traffic light creates prove startup-delay time and end-lag-time. The conventional traffic light loses the function of optimal cycle. And so, 30-45% of conventional traffic cycle is not matched to the present traffic cycle. In this paper proposes electro sensitive traffic light using fuzzy look up table method which will reduce the average vehicle waiting time and improve average vehicle speed. Computer simulation results prove that reducing the average vehicle waiting time which proposed considering passing vehicle length for optimal traffic cycle is better than fixed signal method which dosen't consider vehicle length.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.1328-1332
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• 2010

The enlargement of existing tunnels is required to cope with problems related to traffic congestion. Sometimes, the tunnel traffic must be maintained through existing tunnels during their reconstruction due to non-availability of detours. And excavation by drill and blasting is desired for widening a hard rock tunnel. In this case, the road must be closed for some period for blasting through analyzing of traffic volume. In this paper, a case study on some traffic countermeasures for tunnel enlargement by blasting was performed. And the traffic flow characteristics of some tunnels in domestic main city were analyzed.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.449-464
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• 2016

The purpose of this study is to test applicability of cut-through roundabouts at a congested intersection and to provide the traffic volume ranges for theirs application. Various test scenarios were developed according to variation of total traffic volume, left-turn ratio to total traffic volume, and ratio of major road traffic volume to minor road traffic volume. In addition, three intersection types of cut-through roundabout, roundabout, and signalized intersection were compared with respect to delay times for each scenario, resulted from the simulation using VISSIM. In case of the ratio of major road traffic volume to minor road traffic volume, 6:4, the delay times of cut-through roundabout decreased up to 30% of left-turn ratio to total traffic volume for 400vphpl, up to 20% for 500vphpl, up to 10% for 600vphpl. In case of the ratio, 7:3, they are the same as 6:4 for 400vphpl, 500vphpl, and 600vphpl but they decreased up to 30% for 300vphpl and up to 10% for 700vphpl. In case of the ratio, 8:2, they are the same as 7:3 for 400vphpl, 500vphpl, and 700vphpl but they were reduced by 10% to 30% for 300vphpl and 20% for 600vphpl. It is concluded that the smaller left-turn ratio to total traffic volume as well as the ratio of minor road traffic volume to major road traffic volume is, the more effective in reducing delay times the cut-through roundabout is. Cut-through roundabouts can be expected to reduce delay times at a signalized intersections with traffic conditions above-mentioned.

• International Journal of Highway Engineering
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• v.18 no.3
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• pp.109-114
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• 2016

PURPOSES : The demand for extending national highways is increasing, but traffic monitoring is hindered because of resource limitations. Hence, this study classified highway segments into 5 types to improve the efficiency of short-term traffic count planning. METHODS : The traffic volume trends of 880 highway segments were classified through R-squared and linear regression analyses; the steadiness of traffic volume trends was evaluated through coefficient of variance (COV), and the normality of the data were determined through the Shapiro-Wilk W-test. RESULTS : Of the 880 segments, 574 segments had relatively low COV and were classified as type 1 segments, and 123 and 64 segments with increasing and decreasing traffic volume trends were classified as type 2 and type 3 segments, respectively; 80 segments that failed the normality test were classified as type 4, and the remaining 39 were classified as type 5 segments. CONCLUSIONS : A theoretical basis for biennial count planning was established. Biennial count is recommended for types 1~4 because their mean absolute percentage errors (MAPEs) are approximately 10%. For type 5 (MAPE =19.26%), the conventional annual count can be continued. The results of this analysis can reduce the traffic monitoring budget.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.110-116
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• 2016

Autonomous vehicles must obey the traffic laws in order to drive actual roads. Traffic signs erected at the side of roads explain the road traffic information or regulations. Therefore, traffic sign recognition is necessary for the autonomous vehicles. In this paper, color characteristics are first considered to detect traffic sign candidates. Subsequently, we establish HOG (Histogram of Oriented Gradients) features from the detected candidate and recognize the traffic sign through a SVM (Support Vector Machine). However, owing to various circumstances, such as changes in weather and lighting, it is difficult to recognize the traffic signs robustly using only SVM. In order to solve this problem, we propose a tracking algorithm with RANSAC-based motion estimation. Using two-point motion estimation, inlier feature points within the traffic sign are selected and then the optimal motion is calculated with the inliers through a bundle adjustment. This approach greatly enhances the traffic sign recognition performance.