• KSCE Journal of Civil and Environmental Engineering Research
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• 제30권1D호
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• pp.45-51
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• 2010

Traffic volume is essential data for traffic control or maintenance and rehabilitation planning. The volume especially with respect to the type of vehicles can facilitate to those road operations. In this research, a method for vehicle classification was developed using skewed sensors which can generate traffic signatures. In order to characterize vehicle types, the method investigates whether the second axle of each vehicle consists of dual tires. The presence of dual tire is determined by the discriminate function obtained from discriminant analysis. The validation using 1,878 vehicles recorded from a highway using a CCTV camera indicated significantly accurate results: 96.92% for class 1, 82.91% for class 3 and 79.13% for class 4.

• Proceedings of the KIEE Conference
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.2962-2964
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• 1999

We know the traffic information about the velocity and position of vehicle by extraction and tracking vehicle from continuosly obtained road image of camera. The conventional method of vehicle detection indicate increment of error due to headlight and taillight in night road image. This paper show such as vehicle detection of binary, Edge detection. amalgamation of image are applied to extract the vehicle, and Kalman filter is adaptive methods for tracking position and velocity of vehicle.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제42권1호
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• pp.181-192
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• 2017

Recently, many researches are carried out for Advanced Driver Assistant Systems(ADAS). Especially, many studies are carried out to analyze the road situation using road images. In order to improve the performance of the road situation analysis, it is necessary to acquire images with appropriate exposure time. In this paper, we design and implement multi exposure smart vehicular camera which provides road traffic information to driver. Proposed device can acquire road traffic information by on-board camera and various sensors. And we propose an auto exposure control algorithm for the road environment to increase accuracy of image recognition. In addition, we also propose the switching ROI method that apply existing ROI techniques to overcome a limited computation power of embedded devices. We developed prototype of multi exposure smart vehicular camera and performed experiments to evaluate proposed auto exposure control algorithm and switching ROI method. The results show that the average accuracy of image recognition increased by 13.45%.

• International Journal of Highway Engineering
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• 제10권3호
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• pp.19-31
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• 2008

Video image processing systems(VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on wide-area detection, i.e., multi-lane surveillance algorithm provide traffic parameters with single camera such as flow and velocity, as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. The objective of this research was to relate traffic safety to VIPS tracking and this paper has developed a computer vision system of monitoring individual vehicle trajectories based on image processing, and offer the detailed information, for example, volumes, speed, and occupancy rate as well as traffic information via tripwire image detectors. Also the developed system has been verified by comparing with commercial VIP detectors.

• Journal of Korean Society of Transportation
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• 제34권1호
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• pp.29-42
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• 2016

Speeding is an important factor in traffic safety. Speed not only affects crash severity, but is also related to the possibility of crash occurrence. This study presents results from an analysis of 27,968 speed violation cases collected from 36 red light and speed enforcement cameras at signalized intersections in the city of Cheongju. Data included details of their violation history such as speeding tickets within a recent 3-year span and their demographic characteristics. The goal of this analysis is to understand the correlation between speed violations and various factors in terms of humans, vehicles and road environments. This study used descriptive statistics and Binary Logistics Regression(BLR) analysis with SPSS 20.0 software. The major results of this study are as follows. First, speed violations occurred at rural and suburban area. Second, about 25.6% of the violators committed to more than 20km/h over a speed limit. Third, the difference between speed violators and normal drivers clearly appeared in location of intersection(urban/rural/suburban area), gender and age. Finally, a statistically significant model(Hosmer and Lemeshow test: 11.586, p-value: 0.171) was developed through the BLR.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제19권3호
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• pp.651-658
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• 2015

Recently, lots of research works have been actively focused on the self-driving car. In order to implement the self-driving car, lots of fusion techniques should be merged and, specially, it is noted that a vehicle-attached camera can provide several useful functionalities such as traffic lights recognition, pedestrian detection, stop-line recognition including simple driving records. Accordingly, as one of the efficient tools for the self-driving car implementation, this paper proposes a mathematical model for estimating effectively the road distance with a vehicle-attached black box camera. The proposed model can be effectively used for estimating the road distance by using the height of black box camera or the widths of the referenced road line and the observed road line. Through several simulations, it is shown that the proposed model is effective in estimating the road distance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제9권2호
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• pp.23-32
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• 2010

Because ROTA(road traffic authority) analyzes the effects of accident reduction based on the data of 1-year after installation of RLC(red light camera), study of accident reduction effects over year after the installation of RLC is very short. This study deals with the traffic accident reduction during 3 years after the installation of RLC. The objective is to analyze the effects of accident reduction by year using EB method. In pursuing the above, the study uses the 951 accident data occurred at the 20 intersections which RLC are installed. The main results analyzed are as follows. First, the safety performance function (SPF) has been developed by the Poisson regression models which are statistically significant. Second, the results of an Empirical Bayes(EB) analyses showed that the accidents were reduced by the range from 2.73 to 38.75% after 1 year, from 6.85 to 47.36% after 2 year, and from 6.04 to 39.31% after 3 year from the installation of RLC.

• Journal of the Korean Institute of Intelligent Systems
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• 제25권1호
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• pp.35-41
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• 2015

When a video surveillance system tracks a specific object, it is very important to get quickly the information of the object through fast image processing. Usually one camera surveillance system for tracking the object made results in various problems such like occlusion, image noise during the tracking process. It makes difficulties on image based moving object tracking. Therefore, to overcome the difficulties the multi video surveillance system which installed several camera within interested area and looking the same object from multi angles of view could be considered as a solution. If multi cameras are used for tracking object, it is capable of making a decision having high accuracy in more wide space. This paper proposes a method of recognizing and tracking a specific object like a car using the homography in which multi cameras are installed at the crossroad.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제17권5호
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• pp.77-87
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• 2018

Traffic Density is the most important of the three primary macroscopic traffic stream parameters, because it is most directly related to traffic demand(Traffic Engineering, 2004). It is defined as the number of existing vehicles within a given distance at a certain time. However, due to weather, road conditions, and cost issues, collecting density directly on the field is difficult. This makes studies of density less actively than those of traffic volume or velocity. For these reasons, there is insufficient attempts on divers collecting methods or researches on the accuracy of measured values. In this paper, we used the 'Density Measuring System' based on the synthesise technology of several camera images as a method to measure density. The collected density value by the 'Density Mesuring System' is selected as the true value based on the density define, and this value was compared with the density calculated by the traditional measurement methods. As a result of the comparison, the density value using the fundamental equation method is the closest to the true value as RMSE shows 1.8 to 2.5. In addition, we investigated some issues that can be overlooked easily such as the collecting interval to be considered on collecting density directly by calculating the moment density and the average density. Despite the actual traffic situation of the experiment site is LOS B, it is difficult to judge the real traffic situation because the moment density values per second are observed max 16.0 (veh/km) to min 2.0 (veh/km). However, the average density measured for 15 minutes at 30-second intervals was 8.3-7.9 (veh/km) and it indicates precisely LOS B.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• 제45권3호
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• pp.165-176
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• 2009

The process of berthing/deberthing operations for entering/leaving vessels in Busan northern harbor was analyzed and evaluated by using an integrated VTS(vessel traffic service) system installed in the ship training center of Pukyong National University, Busan, Korea. The integrated VTS system used in this study was consisted of ARPA radar, ECDIS(electronic chart display and information system), backup(recording) system, CCTV(closed-circuit television) camera system, gyro-compass, differential GPS receiver, anemometer, AIS(automatic identification system), VHF(very high frequency) communication system, etc. The network of these systems was designed to communicate with each other automatically and to exchange the critical information about the course, speed, position and intended routes of other traffic vessels in the navigational channel and Busan northern harbor. To evaluate quantitatively the overall dynamic situation such as maneuvering motions for target vessel and its tugboats while in transit to and from the berth structure inside a harbor, all traffic information in Busan northern harbor was automatically acquired, displayed, evaluated and recorded. The results obtained in this study suggest that the real-time tracking information of traffic vessels acquired by using an integrated VTS system can be used as a useful reference data in evaluating and analyzing exactly the dynamic situation such as the collision between ship and berth structure, in the process of berthing/deberthing operations for entering/leaving vessels in the confined waters and harbor.