• Journal of the Korean Society of Safety
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• v.23 no.2
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• pp.65-71
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• 2008

As the interest in traffic safety has been increasing recently, social movement is being made to reduce the number of traffic accidents and the view on improving the mobility of the existing roads is being converted into on establishing traffic safety as a priority. The increase of traffic accidents related to an intersection in a state that traffic accidents are decreasing overall may suggests the necessity to investigate the specific causes. In addition, we have to consider them when establishing the measures against traffic accidents in a intersection by investigating and analyzing the influences and factors that may affect traffic accidents. To induce the accident severity model, we collected the factors that affect accidents and then applied the Poisson Regression Model among nonlinear regression analysis by verifying the distribution of variables. As a result of the analysis, it turned out that the volume of traffic on main roads, the right turn ratio on sub-roads, the number of ways out on sub-roads, the number of exclusive roads for a left turn, the signals for a right turn on main roads, and an intersect angle were the factors that affect the accident severity.

• Journal of the Korean Society of Safety
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• v.33 no.3
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• pp.77-82
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• 2018

This paper aims to analyze the accident based on changing patterns of traffic culture index. For this purpose, this paper particularly focuses on classifying the traffic culture patterns and developing the traffic accidents using panel count data model. The main results are as follows. First, the traffic culture patterns are divided into 'increasing', 'decreasing' and 'other' patterns. The null hypotheses that the number of accident are the same over patterns are rejected. Second, 4 fixed effect negative binomial models which are all statistically significant are developed. Third, the regions with 'increasing' pattern are analyzed to be mostly the counties, and to demand the traffic law enforcement. Fourth, the regions with 'decreasing' pattern are evaluated to be mainly the districts and to require such the traffic culture as turn signal usage. Finally, the regions with 'other' pattern are analyzed to be mostly the cities and to ask for enhancing the level of traffic culture.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.4
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• pp.425-432
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• 2009

Recently, reduction of road traffic noise in residential buildings has become one of the most important subjects. To reduce the road traffic noise, noise impact assessment by the road traffic prediction model is required before building construction. For reasonable road traffic noise prediction, it is required to analysis of various factors in road traffic prediction models. This paper was studied the road traffic noise propagation factors such as distance from road to building, receiver height, alignment angle of building and reflection coefficient of the building facade by two calculation models, RLS-90 and CRTN. The result showed that noise reduction was generally higher at bottom stories by ground absorption effect. The reflection coefficient of the building facade was affect of additional sound pressure level by facade reflecting. And alignment angle of building at $90^{\circ}$ was performed effective noise reduction better than $0^{\circ}$.

• Journal of Korean Society of Transportation
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• v.11 no.1
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• pp.67-86
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• 1993

A formulation of dynamic traffic assignment between multiple origins and single destination was first introduced in 1987 by Merchant and Nemhauser, and then expanded for multiple destination in the late 1980's (Carey, 1987). Based on behavioral choice theory which provides proper demand elasticities with respect to changes in policy variables, traffic phenomena can be analysed more realistically, especially in peak periods. However, algorithms for these models are not well developed so far(working with only small toy network) and solutions of these models are not unique. In this paper, a new model is developed which keeps the simplicity of static models, but provides the sensitivity of dynamic models with changes of O-D flows over time. It can be viewed as a joint departure time and route choice model, in the given time periods(6-7, 7-8, 8-9 and 9-10 am). Standard multinomial logit model has been used for simulating the choice behavior of destination, mode, route and departure time within a framework of the incremental network assignment model. The model developed is workable in a PC 386 with 175 traffic zones and 3581 links of Seoul and tested for evaluating the exclusive use of Namsan tunnel for HOV and the left-turn prohibition. Model's performance results and their statistical significance are also presented.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.65-73
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• 2015

PURPOSES : This study tries to develop the accident models of 4-legged signalized intersections in Busan Metropolitan city with random parameter in count model to understanding the factors mainly influencing on accident frequencies. METHODS : To develop the traffic accidents modeling, this study uses RP(random parameter) negative binomial model which enables to take account of heterogeneity in data. By using RP model, each intersection's specific geometry characteristics were considered. RESULTS : By comparing the both FP(fixed parameter) and RP modeling, it was confirmed the RP model has a little higher explanation power than the FP model. Out of 17 statistically significant variables, 4 variables including traffic volumes on minor roads, pedestrian crossing on major roads, and distance of pedestrian crossing on major/minor roads are derived as having random parameters. In addition, the marginal effect and elasticity of variables are analyzed to understand the variables'impact on the likelihood of accident occurrences. CONCLUSIONS : This study shows that the uses of RP is better fitted to the accident data since each observations'specific characteristics could be considered. Thus, the methods which could consider the heterogeneity of data is recommended to analyze the relationship between accidents and affecting factors(for example, traffic safety facilities or geometrics in signalized 4-legged intersections).

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.193-206
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• 2002

A signal optimization model is proposed by applying the Cell-Transmission Model(CTM) as an embedded traffic flow model to estimate a system-optimal signal timing plan in a transportation network composed of signalized intersections. Beyond the existing signal-optimization models, the CTM provides appropriate theoretical and practical backgrounds to simulate oversaturation phenomena such as shockwave, queue length, and spillback. The model is formulated on the Mixed-Integer Programming(MIP) theory. The proposed model implies a system-optimal in a sense that traffic demand and signal system cooperate to minimize the traffic network cost: the demand departing from origins through route choice behavior until arriving at destinations and the signal system by calculating optimal signal timings considering the movement of these demand. The potential of model's practical application is demonstrated through a comparison study of two signal control strategies: optimal and fixed signal controls.

• Journal of Korean Society of Transportation
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• v.14 no.1
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• pp.101-116
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• 1996

Increased attention has been paid in recent years to the need of traffic management for alleviating urban traffic congestion. This paper presents a discrete event modeling and simulation framework for analyzing the traffic flow. Traffic simulation models can be classified as being either microscopic and macroscopic models. The discrete event modeling and simulation technique can be basically employed to describe the macroscopic traffic simulation model. To do this, we have employed the System Entity Structure/Model Base (SES/MB) framework which integrates the dynamic-based formalism of simulation with the symbolic formalism of AI. The SES/MB framework supports to hierarchical, modular discrete event modeling and simulation environment. We also adopt the Symbolic DEVS (Discrete Event System Specification) to developed the automated analysis methodology for generating optimal signal light policy. Several simulation tests will demonstrates the techniques.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.301-303
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• 2004

In this work, we develop on-line traffic prediction algorithm for real-time VBR traffic. There are a number of important issues: (i) The traffic prediction algorithm should exploit the stochastic characteristics of the underlying traffic and (ii) it should quickly adapt to structural changes in underlying traffic. GOP ARIMA model effectively addresses this issues and it is used as basis in our bandwidth prediction. Our prediction model deploy Kalman filter to incorporate the prediction error for the next prediction round. We examine the performance of GOP ARIMA based prediction with linear prediction with LMS and double exponential smoothing. The proposed prediction algorithm exhibits superior performam againt the rest.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.307-313
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• 2011

In this paper, we compare performance of three models. The Holt-Winters, FARIMA and ARGARCH models, are used in predicting internet traffic data for analysis of traffic characteristics. We first introduce the time series models and apply them to real traffic data to forecast. Finally, we examine which model is the most suitable for explaining the long memory, the characteristics of the traffic material, and compare the respective prediction performance of the models.

• Journal of Sensor Science and Technology
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• v.17 no.3
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• pp.236-244
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• 2008

The Korean government is building several futuristic cities, ubiquitous City (u-City), with the latest information technology (IT) infrastructure and "ubiquitous" environment. In the "u-City", Intelligent Transportation System (ITS) will be one of the important services. This study proposed a traffic responsive urban traffic control system applicable in those u-City, using RFID (Radio Frequency Identification) technology to get traffic information. And, we proposed a predictive control model using the real time traffic information achieved from the proposed system. A simulation example is provided to demonstrate the applicability of the proposed system and model.