• International Journal of Highway Engineering
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• v.17 no.4
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• pp.107-115
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• 2015

PURPOSES: This study analyzes the characteristics of traffic flow on freeway sections under daytime and nighttime conditions to improve traffic safety, and suggests a method to estimate an accurate freeway capacity value that reflects these characteristics. METHODS : The trends and differences in capacity were investigated using comprehensive field data collected under both daytime and nighttime conditions on freeway sections with designated speeds of 80, 100, and 120 kph. RESULTS : The capacity values under nighttime driving conditions were reduced by 3.3%, 6.9%, and 8.8% at 80, 100, and 120 kph, respectively. Several nighttime adjustment factors were deduced for each designated speed category from the analysis results. CONCLUSIONS : It is expected that more accurate capacity values can be estimated for freeway sections under nighttime conditions by applying the resulting adjustment factors. In addition, traffic safety will be improved through the increased efficiency of traffic management on these freeway sections.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.437-439
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• 2006

Actually, The present traffic accident detection system is subsisting limitation of accurate distinction under the crowded condition at intersection because the system defend upon mainly the image information at intersection and digital image processing techniques nearly all. To complement this insufficiency, this article aims to estimate the level of present technology and a realistic possibility by analyzing the acoustic characteristic of crash sound that we have to investigate for improvement of traffic accident detection rate at intersection. The skid sound of traffic accident is showed the special pattern at 1[kHz])${\sim}$3[kHz] bandwidth when vehicles are almost never operated in and around intersection. Also, the frequency bandwidth of vehicle crash sound is showed sound pressure difference oyer 30[dB] higher than when there is no occurrence of traffic accident below 500[Hz].

• Smart Media Journal
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• v.5 no.4
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• pp.75-82
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• 2016

Although Korea's economic and domestic automobile market through the change of road environment are growth, the traffic accident rate has also increased, and the casualties is at a serious level. For this reason, the government is establishing and promoting policies to open traffic accident data and solve problems. In this paper, describe the method of predicting traffic accidents by eliminating the class imbalance using the traffic accident data and constructing the Hybrid Model. Using the original traffic accident data and the sampled data as learning data which use FP-Growth algorithm it learn patterns associated with traffic accident injury severity. Accordingly, In this paper purpose a method for predicting the severity of a victim of a traffic accident by analyzing the association patterns of two learning data, we can extract the same related patterns, when a decision tree and multinomial logistic regression analysis are performed, a hybrid model is constructed by assigning weights to related attributes.

• Journal of the Society of Disaster Information
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• v.13 no.4
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• pp.570-576
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• 2017

Trucks take up more portions than cars on highways. Due to this, road use relatively diminish and it serves locally as a threatening factor to nearby drivers. Baggage car accident has distinct characteristics so that it needs the application of different analysis opposed to ordinary accidents. Accident prediction model, one of accident analyses, is used to predict the numbers of accident in certain parts, establish traffic plans as well as accident prevention methods, and diagnose the danger of roads. Thus, this study aims to apply the accident rate of baggage car on highways and calculate the correction factor to be put in the accident prediction models. Accident data based on highway was collected and traffic amounts and accident documents between 2014 and 2016 were utilized. The author developed an accident prediction model based on numbers of annual accidents and set mean annual and daily traffic amounts. This study intends to identify the practical accident prediction model on highway and present an appropriate solution by comparing the prediction model in accords with the accident rate between baggage cars.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.307-320
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• 2017

The objective of this study is to identify the effectiveness of ESC(Electronic Stability Control) based on a meta analysis technique. Accident Rate, Fatal Crash Rate, Loss of Control Crash Rate were set as indexes of traffic safety evaluation. Also, reviews on the effectiveness of ESC were collected using keyword, 'ESC'. As a result, the Effect size of accident rate odd ratio was 0.90. When ESC system was applied on vehicles, accident rate decreased by 10%. Also, the Effect size of fatal crash rate odd ratio was 0.64. When ESC system was applied on vehicles, fatal crash rate decreased by 36%. Lastly, the Effect size of loss of control crash rate odd ratio was 0.73. When ESC system was applied on vehicles, loss of control crash rate decreased by 27%. The outcome of this study would be effectively used for developing polices and regulations for ESC installation obligation of commercial vehicles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.240-259
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• 2020

Analyzing network traffic is the basis of dealing with network security issues. Most of the network security systems depend on the feature selection of network traffic data and the detection ability of malicious traffic in network can be improved by the correct method of feature selection. An FAFS method, which is short for Fuzzy Association Feature Selection method, is proposed in this paper for network malicious traffic detection. Association rules, which can reflect the relationship among different characteristic attributes of network traffic data, are mined by association analysis. The membership value of association rules are obtained by the calculation of fuzzy reasoning. The data features with the highest correlation intensity in network data sets are calculated by comparing the membership values in association rules. The dimension of data features are reduced and the detection ability of malicious traffic detection algorithm in network is improved by FAFS method. To verify the effect of malicious traffic feature selection by FAFS method, FAFS method is used to select data features of different dataset in this paper. Then, K-Nearest Neighbor algorithm, C4.5 Decision Tree algorithm and Naïve Bayes algorithm are used to test on the dataset above. Moreover, FAFS method is also compared with classical feature selection methods. The analysis of experimental results show that the precision and recall rate of malicious traffic detection in the network can be significantly improved by FAFS method, which provides a valuable reference for the establishment of network security system.

• Journal of Satellite, Information and Communications
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• v.5 no.2
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• pp.87-91
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• 2010

The IEEE 802.15.4 and IEEE 802.15.7 standard are the typical of low rate wireless and Visible Light Wireless personal area networks. Its Medium Access Control protocol can support the QoS traffic flows for real-time application through guaranteed time slots (GTS) in beacon mode. However, how to achieve a best allocation scheme is not solved clearly. The current analytical models of IEEE 802.15.4 MAC reported in the literature have been mainly developed under the assumption of saturated traffic or non-bursty unsaturated traffic conditions. These assumptions don't capture the characteristics of bursty multimedia traffic. In this paper, we propose a new analytical model for GTS allocation with burst Markov modulated ON-OFF arrival traffic.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.4
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• pp.410-416
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• 2009

In recent years, the rollover accident of large class of vehicles has become important safety issue. Even though the rollover form a small percentage of all traffic accidents, they have a fatal effect upon the driver and passenger. Among the traffic accidents occurred in driving, the rollover is the major cause of traffic fatalities. Therefore, it is required to develop the analytical and experimental techniques for predicting rollover propensity of vehicles and also to improve the vehicle suspension design in the viewpoint of rollover resistance. In this study, the parameter sensitivities for the roll angle of SUV suspension are analyzed, and then the determined design parameters are optimized by using the regression model function of the response surface methods. The analysis results show that the roll angle of the optimized vehicle is decreased as compared with the initial vehicle and also the rollover possibility is decreased when the roll rate of the front suspension is larger than the roll rate of the rear suspension.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.330-341
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• 2007

This work analyzes the performance of the parallel packet switch (PPS) with a sliding window (SW) method. The PPS involves numerous packet switches that operate independently and in parallel. The conventional PPS dispatch algorithm adopts a round robin (RR) method. The class of PPS is characterized by deployment of parallel low-speed switches whose all memory buffers run more slowly than the external line rate. In this work, a novel SW packet switching method for PPS, called SW-PPS, is proposed. The SW-PPS employs memory space more effectively than the existing PPS using RR algorithm. Under identical Bernoulli and bursty data traffic, the SW-PPS provided significantly improved performance when compared to PPS with RR method. Moreover, this investigation presents a novel mathematical analytical model to evaluate the performance of the PPS using RR and SW method. Under various operating conditions, our proposed model and analysis successfully exhibit these performance characteristics including throughput, cell delay, and cell drop rate.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.7
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• pp.309-316
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• 2005

In this paper we analyzed a dangerous failure and a safety requirement based on HIA (Hazard Identification and Analysis) of an interface model between CTC (Centralized Traffic Control) system and El (Interlocking) system, and assigned SU (Safety Integrity Level) by way of an risk estimation of the interface, which employed PHA (Preliminary Hazard Analysis) for the interface of the track control system, being managed as separated system between the centralized traffic control system and the interlocking system, An estimation which satisfies a safety reference of the international standard has been achieved through a quantification of the system failure rate and the dangerous failure rate of the interface model.