• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.2D
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• pp.129-136
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• 2012

In the US, Japan and Germany the Aerial-Based Vehicle Detection System, which collects real-time traffic data using the Unmanned Aerial Vehicle (UAV), helicopters or fixed-wing aircraft has been developed for the last several years. Therefore, this study was done to find out whether the Aerial-Based Vehicle Detection System could be used for real-time traffic data collection. For this purpose the study was divided into two parts. In the first part the possibility of retrieving real-time traffic data such as travel speed from the aerial photographic image using the image processing technique was examined. In the second part the quality of the retrieved real-time traffic data was examined to find out whether the data are good enough to be used as traffic information source. Based on the results of examinations we could conclude that it would not be easy for the Aerial- Based Vehicle Detection System to replace the present Vehicle Detection System due to technological difficulties and high cost. However, the system could be effectively used to make the emergency traffic management plan in case of incidents such as abrupt heavy rain, heavy snow, multiple pile-up, etc.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.48 no.1
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• pp.29-39
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• 2012

Currently, environment-friendly and sustainable fisheries are one of the major issues among fisheries authorities. A variety of alternative management policies and projects are going on to enhance fisheries management systems and fishery resources such as a TAC management program and a VDS (Vessel Day Scheme) management scheme for distant water fishing nations in Western and Central Pacific Fisheries Commission (WCPFC) convention area. These kinds of efforts among fisheries management authorities are aimed at limiting fishing capacity or fishing power. In terms of fisheries management, Fishing capacity and fishing power have increased the importance of the impact on a fishery and level of the resources. Increased fishing capacity and fishing power have caused not only depletion of fisheries resource, but also additional fishing cost. therefore, there is a clear need for authorities to manage fishing capacity and fishing power. It is also help ensure the conservation and sustainability of the fishery resources. Because of lack of data, absolute fishing power is difficulty to measure. The notion of relative fishing power is frequently used. In this study, relative fishing power was assessed using Mastuda (1991) method for fishing power index. The raw data for assessment was based on fishermen's logbook data from sampled fishing vessels in coastal snow crab gillnet fishery. Data Envelopment Analysis (DEA) method was used to assess fishing capacity. DEA is a linear programming methodology to measure the efficiency of a set of entities called Decision-Making Units (DMUs). It was recommended by FAO for assessing capacity in fisheries.

• Journal of Korean Society of Transportation
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• v.34 no.4
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• pp.354-372
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• 2016

This study identified factors affecting the crash severity at freeway work zones. A nice feature of this study was to take into account the characteristics of work zone traffic management in analyzing traffic safety concerns. In addition to crash records, vehicle detection systems (VDS) data and work zone historical data were used for establishing a dataset to be used for statistical analyses based on an ordered probit model. A total of six safety improvement strategies for freeway work zones, including traffic merging method, guidance information provision, speed management, warning information systems, traffic safety facility, and monitoring of effectiveness for countermeasures, were also proposed.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.2 no.3
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• pp.10-16
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• 1991

The error networks due to the measuring systems and the test fixture must be previously calibrated in order to characterize the microwave devices. In this paper, it is presented a new method to characterize the error networks in which only two different microstrip lines are used for the calibration. Once each length of two calibrat- ing microstrip lines is accurately defined, the calibrated data can be easily obtained without acknowledgement for the propagation constant. The end effect is not considered when fabricated the microstrip lines used to calibration. The ATF13736 GaAs MESFET is characterized by means of the calibrating procedure with this method. The range of measuring frequency is 2 to 18 GHz, and the bias voltage and current are $V_{DS}$ =2.5V, $I_{DS}$ =20mA, respectively. Compared the calibrated data with data sheet, it is showed that the magnitude is nearly agreed with each other and the phase is deviated by 0.1 to 12 degrees in lower frequencies.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.522-530
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• 2014

Spatio-temporal congestion evolution pattern can be reproduced using the VDS(Vehicle Detection System) historic speed dataset in the TMC(Traffic Management Center)s. Such dataset provides a pool of spatio-temporally experienced traffic conditions. Traffic flow pattern is known as spatio-temporally recurred, and even non-recurrent congestion caused by incidents has patterns according to the incident conditions. These imply that the information should be useful for traffic prediction and traffic management. Traffic flow predictions are generally performed using black-box approaches such as neural network, genetic algorithm, and etc. Black-box approaches are not designed to provide an explanation of their modeling and reasoning process and not to estimate the benefits and the risks of the implementation of such a solution. TMCs are reluctant to employ the black-box approaches even though there are numerous valuable articles. This research proposes a more readily understandable and intuitively appealing data-driven approach and developes an algorithm for identifying congestion patterns for recurrent and non-recurrent congestion management and information provision.

• International Journal of High-Rise Buildings
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• v.3 no.2
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• pp.155-165
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• 2014

This study measured and compared the variation of ventilation rate and fan energy consumption according to various control strategies after installing wireless sensor-based pilot ventilation system in order to verify the applicability of demand-controlled ventilation (DCV) strategy that was efficient ventilation control strategy for underground parking lot. The underground parking lot pilot ventilation system controlled the ventilation rate by directly or indirectly tracking the traffic load in real-time after sensing data, using vehicle detection sensors and carbon monoxide (CO) and carbon dioxide ($CO_2$) sensor. The ventilation system has operated for 9 hours per a day. It responded real-time data every 10 minutes, providing ventilation rate in conformance with the input traffic load or contaminant level at that time. A ventilation rate of pilot ventilation system can be controlled at 8 levels. The reason is that a ventilation unit consists of 8 high-speed nozzle jet fans. This study proposed vehicle detection sensor based demand-controlled ventilation (VDS-DCV) strategy that would accurately trace direct traffic load and CO sensor based demand-controlled ventilation (CO-DCV) strategy that would indirectly estimate traffic load through the concentration of contaminants. In order to apply DCV strategy based on real-time traffic load, the minimum required ventilation rate per a single vehicle was applied. It was derived through the design ventilation rate and total parking capacity in the underground parking lot. This is because current ventilation standard established per unit floor area or unit volume of the space made it difficult to apply DCV strategy according to the real-time variation of traffic load. According to the results in this study, two DCV strategies in the underground parking lot are considered to be a good alternative approach that satisfies both energy saving and healthy indoor environment in comparison with the conventional control strategies.

• Atmosphere
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• v.31 no.2
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• pp.157-170
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• 2021

To investigate the effect of snowfall on the traffic of general roads in Gangwon-do, case analysis was performed in Gangneung, Pyeongchang, and Chuncheon using ASOS (Automated Synoptic Observing System) snowfall data and VDS (Vehicle Detector System) traffic data. First, we analyzed how much the traffic volume and speed decrease in snowfall cases on regional roads compared to non-snow cases, and the characteristics of monthly reduction due to snowfall were investigated. In addition, Pearson correlation analysis and regression analysis were performed to quantitatively grasp the effect of snowfall on traffic volume and speed, and sensitivity tests for snowfall intensity and cumulative snowfall were performed. The results showed that the amount of snowfall caused decrease both in the traffic volume and speed from usual (non-snowfall) condition. However, the trend was different by region: The decrease rate in traffic volume was in the order of Gangneung (17~22%), Chuncheon (14~17%), and Pyeongchang (11~14%). The decrease rate in traffic speed was in the order of Chuncheon (9~10%), Gangneung (8~9%), Pyeongchang (5~6%). No significant results were found in the monthly decrease rate analysis. In all regions, traffic volume and speed showed a negative correlation with snowfall. It was confirmed that the greater the amount of traffic entering the road, the greater the slope of the trend line indicating the change in snowfall due to the traffic volume. As a result of the sensitivity test for snowfall intensity and cumulative snowfall, the snowfall information at intervals of 6-hours was the most significant.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.55-76
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• 2000

We propose a general solution methodology for identifying the optimal aggregation interval sizes as a function of the traffic dynamics and frequency of observations for four cases : i) link travel time estimation, ii) corridor/route travel time estimation, iii) link travel time forecasting. and iv) corridor/route travel time forecasting. We first develop statistical models which define Mean Square Error (MSE) for four different cases and interpret the models from a traffic flow perspective. The emphasis is on i) the tradeoff between the Precision and bias, 2) the difference between estimation and forecasting, and 3) the implication of the correlation between links on the corridor/route travel time estimation and forecasting, We then demonstrate the Proposed models to the real-world travel time data from Houston, Texas which were collected as Part of the Automatic Vehicle Identification (AVI) system of the Houston Transtar system. The best aggregation interval sizes for the link travel time estimation and forecasting were different and the function of the traffic dynamics. For the best aggregation interval sizes for the corridor/route travel time estimation and forecasting, the covariance between links had an important effect.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.13-22
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• 2009

Recently, DSRC technology is used in the various fields such as parking system, BIS, ETC, etc. This paper suggests a traffic information system using this DSRC technology. The traffic information processing based on point detection using existing vehicle detection equipment is the system in which a collection and a service are operated separately while the traffic information system based on the link detection using DSRC is able to collect and provide the traffic information through the communication between RSE and OBU. The speed of a traffic congestion is high on the process converted from a point passing speed to a link average speed because the vehicle detection equipment makes the link traffic information into the point information. When the condition of traffic is deteriorated, traffic speed of the vehicle detection equipment becomes higher than DSRC. Especially, in this system, deflection by data of the traffic speed of the traffic information system is much decreased, and the unexpected condition detection and traffic condition are provided promptly.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.52 no.4
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• pp.356-363
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• 2016

To suggest more efficient fishing operation, it was analyzed using five years (2011~2015) catch data of six Korean-flagged tuna purse seiners (with 1000 mt of haul capacity) operating in the western and central Pacific Ocean. In terms of annual total catch, it presented a two-year cycle of variation on catch, showing that catches of 2012, 2014 and 2015 were high, whereas those of 2011 and 2013 were low. The proportions on fishing effort of associated set were around 21.9~30.8% having 21.5~45.0% of total catch. In this study, there was no significant difference between catches of unassociated set and associated set. When considered having good fishing conditions, fishing activities were concentrated in the areas of Papua New Guinea (PNG) and Kiribati, while it showed that fishing ground spreaded out to the areas of not only PNG and Kiribati but also Federated States of Micronesia (FSM), Tuvalu and Solomon islands. The average number of fishing days was 271 with a range of 246~285. As restriction on fishing operation such as reduction of fishing days and higher fishing fee are expected to strengthen, the result of this study will be helpful to select more efficient fishing methods for purse seine fishery based on fishing conditions.