• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.47-54
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• 2021

The number of freeway traffic accidents in Korea is about 4,000 as of 2020, and deaths per traffic accident is about 3.7 times higher than other roads due to non-recurring congestion and high driving speed. Most of the accident types on freeways are side and rear-end collisions, and one of the main factors is hazard traffic flow caused by merge, diverge and accidents. Therefore, the hazard traffic flow, which appears in a continuous flow such as a freeway, can be said to be important information for the driver to prevent accidents. This study tried to classify hazard traffic flows, such as the speed change point and the section where the speed difference by lane, using individual vehicle information. The homogeneous segment of speed was classified using spatial separation based on geohash and space mean speed that can indicate the speed difference of individual vehicles within the same section and the speed deviation between vehicles. As a result, I could extract the diverging influence segment and the hazard traffic flow segment that can provide dangerous segments information of freeways.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.41-47
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• 2006

In this study, the influences of environmentally friendly visual and auditory information on traffic noise perception were surveyed by the using electroencephalogram Green rural region image and CBD image in urban city were used as visual informations. And traffic noise, signal and environmental music were used to detect the impact on electroencephalogram variance. It was revealed that green rural region image caused a-wave ratio increase about 10% and environmental music increased $\alpha$-wave ratio approximately $40{\sim}50%$. The results of this study improved that environmentally friendly visual and auditory information had an effect on decreasing traffic noise loudness to some extents.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.2 s.119
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• pp.160-167
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• 2007

In this study, the influences of environmentally friendly visual and auditory information on traffic noise perception were surveyed by the using electroencephalogram. Green rural region image and CBD (central business district) image in urban city were used as visual informations. And traffic noise, signal and environmental music were used to detect the impact on electroencephalogram variance. It was revealed that green rural region image caused ${\alpha}-wave$ ratio increase about 10% and environmental music increased ${\alpha}-wave$ ratio approximately $40{\sim}50%$. The results of this study improved that environmentally friendly visual and auditory information had an effect on decreasing traffic noise loudness to some extents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4887-4907
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• 2017

Accurate traffic flow forecasting is critical to the development and implementation of city intelligent transportation systems. Therefore, it is one of the most important components in the research of urban traffic scheduling. However, traffic flow forecasting involves a rather complex nonlinear data pattern, particularly during workday peak periods, and a lot of research has shown that traffic flow data reveals a seasonal trend. This paper proposes a new traffic flow forecasting model that combines seasonal relevance vector regression with the hybrid chaotic simulated annealing method (SRVRCSA). Additionally, a numerical example of traffic flow data from The Transportation Data Research Laboratory is used to elucidate the forecasting performance of the proposed SRVRCSA model. The forecasting results indicate that the proposed model yields more accurate forecasting results than the seasonal auto regressive integrated moving average (SARIMA), the double seasonal Holt-Winters exponential smoothing (DSHWES), and the relevance vector regression with hybrid Chaotic Simulated Annealing method (RVRCSA) models. The forecasting performance of RVRCSA with different kernel functions is also studied.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.187-196
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• 2017

It is urgent to prepare countermeasures for traffic congestion problems of Korea's metropolitan area where central functions such as economic, social, cultural, and education are excessively concentrated. Most users of public transportation in metropolitan areas including Seoul use the traffic cards. If various information is extracted from traffic big data produced by the traffic cards, they can provide basic data for transport policies, land usages, or facility plans. Therefore, in this study, we extract valuable information such as the subway passengers' frequent travel patterns from the big traffic data provided by the Seoul Metropolitan Government Big Data Campus. For this, we use a Hadoop (High-Availability Distributed Object-Oriented Platform) to preprocess the big data and store it into a Mongo database in order to analyze it by a sequential pattern data mining technique. Since we analysis the actual big data, that is, the traffic cards' data provided by the Seoul Metropolitan Government Big Data Campus, the analyzed results can be used as an important referenced data when the Seoul government makes a plan about the metropolitan traffic policies.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.2
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• pp.9-16
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• 2022

The nodes constituting the vehicle ad hoc network (VANET) are vehicles moving along the road and road side units (RSUs) installed around the road. The vehicle ad hoc network is used to collect the status, speed, and location information of vehicles driving on the road, and to communicate with vehicles, vehicles, and RSUs. Today, as the number of vehicles continues to increase, urban roads are suffering from traffic jams, which cause various problems such as time, fuel, and the environment. In this paper, we propose a method to solve traffic congestion problems on urban roads and demonstrate that the method can be applied to solve traffic congestion problems through performance evaluation using two typical protocols of vehicle ad hoc networks, AODV and GPSR. The performance evaluation used ns-2 simulator, and the average number of traffic jams and the waiting time due to the average traffic congestion were measured. Through this, we demonstrate that the vehicle ad hoc-based traffic congestion management technique proposed in this paper can be applied to urban roads in smart cities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.389-391
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• 2021

Traffic regulations are expanding to prevent traffic accidents for people's safety, but traffic accidents are not decreasing. In this study, the probability of traffic accidents occurring at a specific time and place is estimated by analyzing various factors such as weather forecast data from the Meteorological Agency, day of the week, time of day, location data, and location information. This study combines objective data on the occurrence of numerous previous traffic accidents with various additional elements not considered in previous studies to derive a more improved traffic accident probability prediction model. The results of this study can be effectively used for various transportation-related services for the safety of people.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.535-538
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• 2012

Recently active research for ITS(Intelligent Transportation System) helps to build for next generation traffic information system at information society. Build the system for sensing a vehicle speed and traffic information on the road. Provide collected data to driver, flow of overall traffic impacts have a good influence. In this study, research for building the platform and development algorithm that provided from other source processing real-time traffic data provides a more reliable real-time traffic data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.125-134
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• 2004

This paper proposes a method for recognition of traffic signs using wavelet transform and shape information from the segmented traffic sign regions. It first segments traffic sign candidate regions by connected component algorithm from binary images, obtained by utilizing the RGB color ratio of each pixel in the image, and then extracts actual traffic sign regions based on their symmetries on X- and Y-axes. In the recognition stage, it utilizes shape information including moment edge correlogram and the number of crossings which concentric circular patterns from region center intersects with frequency information extracted by wavelet transform It finally performs recognition by measuring similarity with the templates in the database. The experimental results show the validity of the proposed method from geometric transformations and environmental factors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.575-596
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• 2009

Facing limited network resources such as bandwidth and processing capability, the Internet will have congestion from time to time. In this paper, we propose a scheme to maximize the total utility offered by the network to the end user during congested times. We believe the only way to achieve our goal is to make the scheme application-aware, that is, to take advantage of the characteristics of the application. To make our scheme scalable, it is designed to be class-based. Traffic from applications with similar characteristics is classified into the same class. We adopted the RED queue management mechanism to adaptively control the traffic belonging to the same class. To achieve the optimal utility, the traffic belonging to different classes should be controlled differently. By adjusting link bandwidth assignments of different classes, the scheme can achieve the goal and adapt to the changes of dynamical incoming traffic. We use the control theoretical approach to analyze our scheme. In this paper, we focus on optimizing the control on two types of traffic flows: TCP and Simple UDP (SUDP, modeling audio or video applications based on UDP). We derive the differential equations to model the dynamics of SUDP traffic flows and drive stability conditions for the system with both SUDP and TCP traffic flows. In our study, we also find analytical results on the TCP traffic stable point are not accurate, so we derived new formulas on the TCP traffic stable point. We verified the proposed scheme with extensive NS2 simulations.