• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.6
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• pp.1059-1068
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• 2016

The current operation method for the AVC (Automatic Vehicle Classification) equipment does not generate vehicle speed, traffic volume and vehicle type information when part of the sensors has failed. Inefficiency of current methods would not use the collected data from the normal sensor. In this study was conducted research on the calculating method at the traffic volume and vehicle speed in the sensor failure AVC equipment. The failure situation of the sensor was classified into 4 types. Calculating the traffic volume and vehicle speed information for each type, and accuracy of these informations were analyzed. Analysis results, traffic volume was possible to calculate a highly accurate value (accuracy: 100%, 98%, 97%). In the case of speed, the accuracy of the calculated speed value reaches a level that can be accepted sufficiently (RMSE value is less than 16.8). So, using the methodology proposed in this study are expected to be able to increase the operational efficiency of the AVC equipment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.134-145
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• 2024

The purpose of this study was to propose a framework for developing test scenarios for issuance of conditional driver's licenses. The framework was composed of five stages. Initially, we reviewed the literature on traffic crash characteristics in terms of accident frequency and severity regarding the main factors of crashes caused by older drivers. In the second stage, the characteristics of crashes attributed to non-elderly, early elderly, and late elderly drivers were analyzed using data obtained from the Traffic Accident Analysis System (TAAS), and crash types for elderly drivers were derived. In the third stage, black box videos of high-risk crash types were analyzed to derive crash stories that described the circumstances in which crashes occurred. In the fourth step, crash situations were classified by rating the types of crash stories derived to develop various scenarios. Step 5 involved creating a scenario by applying the PEGASUS 5-Layer format, which has recently been used to develop test scenarios for autonomous vehicles. The results of this study are expected to be used as a basis for developing driving ability evaluation scenarios for the issuance of conditional driver's licenses.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.58-70
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• 2019

In the case of a pedestrian traffic accident, it has a large-scale danger directly connected by a fatal accident at the time of the accident. The domestic ITS is not used for intelligent risk classification because it is used only for collecting traffic information despite of the construction of good quality traffic infrastructure. The CNN based pedestrian detection classification model, which is a major component of the proposed system, is implemented on an embedded system assuming that it is installed and operated in a restricted environment. A new model was created by improving YOLO's artificial neural network, and the real-time detection speed result of average accuracy 86.29% and 21.1 fps was shown with 20,000 iterative learning. And we constructed a protocol interworking scenario and implementation of a system that can connect with the ITS. If a pedestrian accident prevention system connected with ITS will be implemented through this study, it will help to reduce the cost of constructing a new infrastructure and reduce the incidence of traffic accidents for pedestrians, and we can also reduce the cost for system monitoring.

• Journal of Korean Society of Transportation
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• v.20 no.6
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• pp.69-80
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• 2002

차로변경이 발생하는 두 가지 상황 즉, 강제 차로 변경과 선택적 차로 변경 중, 선택적 차로변경 상황에서 운전자가 수락 가능한 간격을 발견했을 때, 차로별 속도 차가 차로 변경 의사결정에 미치는 영향을 모사할 수 있는 모형식을 추정하였다. 즉, 선택적 차로 변경은 운전자의 차로 변경 여부에 대한 상황판단과 함께 목적 차로의 간격 수락여부에 대한 의사결정으로 이루어지는데, 본 논문에서는 목적 차로에 수락 가능한 간격이 존재할 경우 차로별 속도차가 운전자의 의사결정에 어떤 영향을 미치는지에 대해 분석하였다. 이를 위해, 운전자 의 의사결정에 영향을 미칠 수 있는 다른 요소 즉, 중차량, 기하구조, 및 합·분류의 영향을 최소화하는 지점을 선택하여 표본조사를 실시하였으며, 보다 설명력 있는 모형식을 얻기 위해 상관분석 등을 수행하여 불필요하다고 생각되는 변수는 제외시켰다. 또한, 운전자의 희망속도와 주행 속도 차에 의한 영향을 반영하기 위해 현 차로 속도를 부가적인 변수로 추가하였으며, 계수추정은 통계패키지인 SAS를 이용하였는데, 자료분석에 있어, 속도차 구간에 따라 다른 간격수락 특성을 보여 차로별 속도차를 0∼2.0m/s구간과 2∼11.52m/s구간으로 나누어 분석을 수행하였다. 분석결과 속도차 0∼2.0m/s구간에서는 속도차가 증가할수록 차로 변경률이 높아졌으나, 2∼11.52m/s구간에서는 오히려 차로 변경률이 낮아지는 것으로 나타났는데, 이는 속도 차의 증감에 대해 운전자로 하여금 차로 변경을 유도하는 요소와 함께 저항하게 하는 요소가 있다는 것을 알 수 있었다. 분석결과. 2.0m/s 이상의 속도차에서 차로변경에 대한 저항이 상대적으로 크게 작용한다는 것을 알 수 있었으며, 도로 설계시 이를 반영하여 도로기하구조 및 안전성 등을 향상시킬 수 있을 것으로 보인다.

• Journal of Korean Society of Transportation
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• v.36 no.3
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• pp.184-194
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• 2018

Recently, the need to introduce bus lines on a welfare basis is increasing as public intervention in bus routes is accelerated through semi-public bus system. The main objective of this study is to establish the concept of PSO (public service obligation) bus line on a welfare basis and propose a classification method of PSO bus line under semi-public bus system. We introduced 3 indexes such as "equity" in terms of bus line distribution, "publicity" in terms of age distribution, and "profitability" in terms of bus operating revenues. On the basis of 3 indexes, we introduced the PSO bus line, which is fair and public, even if it is not profitable. Based on the concept established in this study, we divided 130 ordinary city bus lines in Busan Metropolitan City into 8 PSO bus lines. Also, considering the positive impact of public buses, which are less profitable, but improve the mobility of residents and secure public community, we suggested the need to introduce public buses in bus service shortage areas.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.63-74
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• 2009

One of the effective countermeasures for preventing traffic accidents is to provide traffic safety warning information to drivers. Provision of warning information would lead to safer driving to avoid accident occurrence. This study investigated the effects of in-vehicle warning information on driver's behavior. A variety of warning information contents using text, sound, and pictograms were prepared for the field experiments. Individual vehicle speed and acceleration data, which represent quantitative drivers' behavior in response to in-vehicle warning information, were collected using differential global positioning systems (DGPS). Statistical analyses including ANOVA and Tukey's pairwise comparison were conducted. It is expected that the results could be invaluable for designing more effective warning information.

• The Korean Journal of Archival Studies
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• no.30
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• pp.125-174
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• 2011

Railway Station in Korea built for purpose to plunder resource and invade China 19 and 20 century early, It functioned as main transportation and important role in local history. However, Since the late 1990s, Railway Station in Korea is facing major changes due to Railroad Improvement and Restructuring plan. Photography is useful way to represent memory and local history about railway station, but Photography Documentation on railroad station were not discussed until now due to indifference of the KORAIL and peculiarities of national security facilities for a long time. This study suggest what is document activities and facilities of railway station, use value analysis about railway station's value firstly. next, this study set each documentation area with value analysis for a basis and present concrete example. finally, this study adapt documentation area and detail to classification scheme and apply activities and facilities of supplement or revision to classification scheme.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.121-132
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• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

• Journal of Platform Technology
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• v.9 no.3
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• pp.44-51
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• 2021

In general, golden time refers to the most important time in the initial response to accidents such as saving lives or extinguishing fires. The golden time varies from disaster to disaster, but is aimed at five minutes in terms of fire and first aid. However, for the actual site, the average dispatch time for ambulances is 9 minutes and the average transfer time is 17.6 minutes, which is quite large compared to the golden time. There are various causes for this delay, but the main cause is traffic jams. In order to solve the problem, the government has established emergency car concession obligations and secured golden time to prioritize ambulances in places with the highest accident rate, but it is not a solution in rush hour when traffic is increasing rapidly. Therefore, this paper proposed a deep learning-based emergency vehicle priority signal system using collected sound data by installing sound sensors on traffic lights and conducted an experiment to classify frequency signals that differ depending on the distance of the emergency vehicle.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.6
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• pp.615-623
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• 2020

In order to prevent the dangers of major marine accidents, it is very important to be aware of in advance through marine incidents in the background of Heinrich's law, formulated by the safety pioneer who is credited with focusing on workplace safety with emphasis on the human element. At least 11 cases of collision accidents occurred in the Busan VTS area from January 1st to December 31st, 2019, and 24 cases of VTS marine incidents were reported during the same period. According to Heinrich's law, there could be many more potentially risky situations besides the 24 reported cases. In this study, the criteria for VTS marine incidents were established through advanced research and a survey of VTS operators, and analysis of 24 cases of VTS marine incidents in the Busan VTS area. Traffic surveys were conducted for three days to identify potentially hazardous situations. According to the survey, there were 216 cases of VTS marine incidents, and within a year, it is estimated there could be about 26,280 cases. Even if conditions such as "missing VHF communication feedback" which is an important cause of marine incidents, are not reflected, there are many potential risks in the VTS area. Thus, it is vital to strengthen the VTS marine incident reporting system.