• Proceedings of the KSRS Conference
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• v.1
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• pp.260-262
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• 2006

One of future remote sensing techniques for transportation application is vehicle detection from the space, which could be the basis of measuring traffic volume and recognizing traffic condition in the future. This paper introduces an approach to vehicle detection using image object segmentation approach. The object-oriented image processing is particularly beneficial to high-resolution image classification of urban area, which suffers from noisy components in general. The project site was Dae-Jeon metropolitan area and a set of true color aerial images at 10cm resolution was used for the test. Authors investigated a variety of parameters such as scale, color, and shape and produced a customized solution for vehicle detection, which is based on a knowledge-based hierarchical model in the environment of eCognition. The highest tumbling block of the vehicle detection in the given data sets was to discriminate vehicles in dark color from new black asphalt pavement. Except for the cases, the overall accuracy was over 90%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.95-109
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• 2017

The golden time of emergency vehicle is directly connected to the public safety. Therefore, national attention has increased to cut down the emergency vehicle's travel time. In order to shorten the intial dispatch time of it, emergency preemption system was installed at five intersections, and after test operation, whether it could be introduced in the country was estimated. We analyzed the effect of the traffic volume, emergency vehicle's travel time, and queue length under preemption and non-preemption. In the verification of the emergency preemption system, it was confirmed that the emergency vehicle's travel time was reduced from 350% to 24% compared to non-preemption system(TOD). In the saturated condition, queue length were remained 15 minutes and near saturated condition was about 30 or 45 minutes. At the non-saturated condition, the queue length's difference between emergency preemption system and general signal was small.

• Korean Journal of Environment and Ecology
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• v.21 no.6
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• pp.526-535
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• 2007

This study was conducted at the Civilian Controlled Zone(CCZ) in the Cherowon from February to March 2004 to investigate the reaction to the vehicles of Red-crowned Cranes(RCC) and White-naped Cranes(WNC) and trade-off of the vehicle interruption with food resources. The for-aging distance from the road of WNC was much closer than that of RCC. The large flocks of cranes' average feeding distance from the road was farther than small flocks of cranes in both species. Cranes showed the reaction, such as alert, walking, running and flying against the vehicle stop and were more sensitive as they were close to the road. The reacting time to the stopping vehicle were reduced as it was farther from the road. The distance of about 250m was a reaction threshold distance against the vehicle stop to both species. The reacting time in the same distance was not different in relation to the traffic volume, but large traffic volume tended to cause cranes to stay far away from the road and not to feed themselves near a traffic congested area. The reason cranes fed themselves on fallen rice grains in spite of the vehicular traffic interruption factor was that there was a high density of the fallen rice grains remaining at the area near a road.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.133-143
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• 2018

Roundabouts are generally installed at which traffic and pedestrian volume is relatively small intersections, and hence traffic can flow one direction around a circular island without traffic lights. A number of researches for roundabout signal metering have been processing ways to deal with operation efficiency drops in conditions of unusual traffic and pedestrian volume increases. However, there is still a shortcoming exists in previous operation algorithm does not consider the hidden vehicles between yield lines and detectors and queueing vehicles in circular lanes. These queueing vehicles between them can be cleared by introducing the queue clearance time. The purpose of this research is developing a real time signal metering operation algorithm by considering the vehicle queue clearance time. The results of varying queue clearance time application show that there is a substantial average vehicle delay reduction in VISSIM Com-Interface simulation. When the total number of entering vehicle is 3,200~4,800 vehicle/hour with varying queue clearance time application 21~50 seconds gives average delay reduction per vehicle by 16.1~71.7%.

• Journal of Urban Science
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• v.11 no.2
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• pp.9-17
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• 2022

The purpose of this study is to develop an index for evaluating the function of a new motorway using the travel distance frequency distribution (TLFD) calculated using the vehicle travel route big data, and to overcome the limitations of the evaluation through the existing traffic volume. The mobility evaluation index of motorways was developed by applying it to the TLFD data table in 2019. The smaller the value of the mobility evaluation index of the link is calculated, the more it is a link with mainly short-distance travel, and the higher the value of the mobility evaluation index, the more it means a link with mainly long-distance travel. The accessibility evaluation index was calculated through the result of the mobility evaluation index of all motorways developed, and all motorways were grouped into three groups using K-means clustering. Group A was found to exist inside a large city and consisted of motorways with many short-distance traffic, Group B was investigated as acting as an arterial between groups, and Group C was classified as a motorway consisting mainly of long-distance traffic connecting large cities and large cities. This study is significant in developing a new motorway function evaluation index that can overcome the limitations of motorway function evaluation through the existing traffic volume. It is expected that this study can be a reasonable comprehensive indicator in the operation and planning process of motorways.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.115-125
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• 2023

This paper relates to the development of CCTV camera posture calibration algorithm that can simultaneously collect traffic information such as traffic volume and speed in the state of view of the CCTV camera set for traffic monitoring. The developed autonomous posture calibration algorithm uses vehicle recognition and tracking techniques to identify the road, and automatically determines the angle of view for the operator's traffic surveillance and traffic information collection. To verify the performance of the proposed algorithm, a CCTV installed on site was used, and the results of the angle of view automatically calculated by the autonomous posture calibration algorithm for the angle of view set for traffic surveillance and traffic information collection were compared.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

• Journal of the Korean Society of Industry Convergence
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• v.4 no.1
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• pp.41-49
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• 2001

This study developed signal optimization algorithm by analyzing vehicle arrival patterns. The major principle of signal optimization is dissipate all queueing vehicle in 1cycle and assign delay time uniformly for all approaches. For this, this study used optimal green time and surplus green time. Optimal green time calculated by estimated traffic volume from vehicle arrival model. Surplus green time defined as the gap of optimal green time and queue dissipated time. And alternative cycle has minimum surplus green time was selected as the optimal cycle. Finally, total delay and average delay per vehicle can be calculated by using queueing theory.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.10 s.241
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• pp.1307-1314
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• 2005

The most important factor of the traffic accident on the wet road is a tire slip caused by hydroplaning. Meanwhile, hydroplaning characteristics are influenced very greatly by the vehicle velocity, so it is very important to reveal the relation between hydroplaning and the vehicle velocity. Since the experiment study is considerably limited, recently the numerical simulation using finite element method(FEM) and finite volume method(FVM) is widely adopted. In this paper, the effect of the vehicle velocity on the hydroplaning characteristics is investigated through the hydroplaning analysis using MSC/Dytran.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.137-148
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• 2005

The position information of individual vehicles on a road at every time instant can be used to analyze the microscopic behaviors of driving of each vehicle. The limited information obtained from previous imaging technology such as traffic volume and interval velocity cannot be used to explore such microscopic traffic conditions. Also, information gathering for the microscopic behaviors by manual analysis of captured video takes large amount of time and man-power. In the paper we develop the rule-based vehicle tracking technology from which the position information of individual vehicles on a road at every time instant can be automatically obtained. Also, we extract the position data of driving vehicles on a road, length of 130m for every 0.05 second, and calculate the velocity of each traced vehicles to compare with the real velocity for the verification of accuracy. In the future, this type of tracking techniques based on video analysis can be widely used to provide the practically important information of road traffic conditions and to analyze the academically important microscopic behaviors of driving patterns.