• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.139-151
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• 2023

This study aims to understand the current status of exemptions for traffic accidents during the return of emergency vehicles and to provide suggestions for improvement. A survey was conducted on 3,500 firefighters to investigate the perception of traffic accidents during the return of emergency vehicles, and responses from 505 participants were analyzed. Based On the demographic characteristics and perception of the participants, frequency analysis and variance analysis were used as research methods to analyze basic statistics and the current situation. The results showed that firefighters have concerns and anxieties about traffic accidents during the return of emergency vehicles, and the need for applying exemptions and enacting explicit legal provisions was statistically confirmed. Based on these results, we suggest a policy for exemptions to improve the preparation for re-deployment and to alleviate the concerns and anxieties of firefighters.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.719-724
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• 2012

A traffic detection system is a device that collects traffic information around an intersection. Most existing traffic detection systems provide very limited traffic information for signal control due to the restriction of vehicle detection area. A signal control scheme determines the transition among signal phases and the time that a phase lasts for. However, the existing signal control scheme do not resolve the traffic congestion effectively since they use restricted traffic information. In this paper, a new traffic detection system with a zone division signal control scheme is proposed to provide correct and detail traffic information and decrease the vehicle's waiting time at the intersection. The traffic detection system obtains traffic information in a way of vehicle-to-roadside communication between vehicles and sensor network. A new signal control scheme is built to exploit the sufficient traffic information provided by the proposed traffic detection system efficiently. Simulation results show that the proposed signal control scheme has 121 % and 56 % lower waiting time and delay time of vehicles at an intersection than other fuzzy signal control scheme.

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.6-15
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• 2022

In this study, a traffic light recognition algorithm was implemented and validated for low-speed special purpose vehicles in an urban environment. Real-time image data using a camera and YOLO algorithm were applied. Two methods were presented to increase the accuracy of the traffic light recognition algorithm, and it was confirmed that the second method had the higher accuracy according to the traffic light type. In addition, it was confirmed that the optimal YOLO algorithm was YOLO v5m, which has over 98% mAP values and higher efficiency. In the future, it is thought that the traffic light recognition algorithm can be used as a dual system to secure the platform safety in the traffic information error of C-ITS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3858-3874
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• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.413-416
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• 2003

This paper proposes an adaptive background image generation method based on the frame difference for traffic monitoring. The performance of the conventional method is limited when there are more vehicles due to traffic Jam. To improve on this, we use frame differencing to separate vehicles from background in frame differencing, we adopt selective approach by using part of the image not considered as vehicle fer extraction of background. The proposed method generates background more efficiently than conventional methods even in the presence of heavy traffic.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.722-728
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• 2003

In this paper, we propose a fuzzy traffic controller of Sugeno`s fuzzy model so as to model the nonlinear characteristics of controlling the traffic light. It use a degree of the traffic congestion of the preceding roads as an input so that it can cope with traffic congestion appropriately, which causes the loss of fuel and our discomfort. First, in order to construct fuzzy traffic controller of Sugeno`s fuzzy model, we model the control process of the traffic light by using Mamdani`s fuzzy model, which has the uniform membership functions of the same size and shape. Second, we make Mamdani`s fuzzy model with the non-uniform membership functions so that it can exactly reflect the knowledge of experts and operators. Last, we construct the fuzzy traffic controller of Sugeno`s fuzzy model by learning from the input/output data, which is retrieved from Mamdani`s fuzzy model with the non-uniform membership functions. We compared and analyzed the fixed traffic light controller, the fuzzy traffic controller of Mamdani`s fuzzy model and the fuzzy traffic controller of Sugeno`s fuzzy model by using the delay time and the proportion of the entered vehicles to the occurred vehicles. As a result of comparison, the fuzzy traffic controller of Sugeno`s fuzzy model showed the best performance.

• Journal of KIISE:Software and Applications
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• v.34 no.11
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• pp.991-1000
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• 2007

A new robust approach to detect vehicles in a single frame of traffic scenes is presented. The method is based on the multi-level shadow classification, which has been shown to have the capability of extracting correct shadow shapes regardless of the operating conditions. The rationale of this classification is supported by the fact that shadow regions underneath vehicles usually exhibit darker gray level regardless of the vehicle brightness and illuminating conditions. Classified shadows provide string clues on the presence of vehicles. Unlike other schemes, neither background nor temporal information is utilized; thereby the performance is robust to the abrupt change of weather and the traffic congestion. By a simple evidential reasoning, the shadow evidences are combined with bright evidences to locate correct position of vehicles. Experimental results show the missing rate ranges form 0.9% to 7.2%, while the false alarm rate is below 4% for six traffic scenes sets under different operating conditions. The processing speed for more than 70 frames per second could be obtained for nominal image size, which makes the real-time implementation of measuring the traffic parameters possible.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.492-498
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• 2021

This study examined how the emissions of pollutants affect the volume of traffic of freight vehicles in the transport sector. Multiple regression analysis was conducted considering several variables, including population by region, area of urban district, GDP, and the number of businesses by industry, e.g., agriculture, forestry, fishery, manufacturing, wholesale, and retail. These variables differ according to the characteristics of the freight vehicles (industry, by the ton). Therefore, it is essential to fully consider the volume of traffic of the specific freight vehicles by region before implementing relevant programs and policies, such as specific restrictions on the operation of vehicles. Some specific areas, in which logistic centers are located have heavy freight traffic, and these centers deserve extra consideration. Thus, in this study, different regional factors that affect the traffic of freight vehicles should be considered before determining the areas that will be subject to restrictions on the operation of these vehicles.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.591-595
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• 1998

This paper proposes a new concept of optimal shortest path algorithm which reduce average vehicle wating time and improve average vehicle speed, Electro sensitive traffic system can extend the traffic cycle when three are many vehicles on the road or it can reduce the traffic cycle when there are small vehicles on the road. But electro sensitive traffic light system doesn't control that kind of function when the average vehicle speed is 10km -20km. Therefore, in this paper to reduce vehicle waiting time we developed design of traffic cycle software tool that can arrive destinination as soon as possible using optimal shortest pass algorithm. Computer simulation result proved 10%-32% reducing average vehicle wating time and average vehicle speed which can select shortest route using built in G.P.S. vehicle is better than not being able to select shortest route function.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.1-16
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• 2011

With the increasing number of vehicles in use in our daily life and the rise of traffic congestion problems, many methods and models have been developed for real time optimisation of traffic lights. Nevertheless, most methods which consider real time physical queue sizes of vehicles waiting for green lights overestimate the optimal cycle length for such real traffic control. This paper deals with the development of a generic hybrid model describing both physical traffic flows and control of signalised intersections. The firing times assigned to the transitions of the control part are considered dynamic and are calculated by a simplified optimisation method. This method is based on splitting green times proportionally to the predicted queue sizes through input links for each new cycle time. The proposed model can be easily translated into a control code for implementation in a real time control system.