• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2D
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• pp.113-118
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• 2010

This paper presents an analysis of the instability phenomenon on motorways, with the aim of arriving at the definition of a control strategy suitable for keeping the flow stable. By using some results of the motorway reliability theory, a relationship and some flow characteristics is obtained, which shows that the existence of a reliability threshold critical for flow stability. The macroscopic flow characteristics corresponding to this threshold are very different in different situations, so that this control of flow stability requires the analysis of speed and density microscopic process surveyed on a cross section of the motorway carriage ways to be controlled. A method is presented, based on integrated moving average(IMA) analysis in real time of these processes, by which it is possible to detect the approach of instability before its effects become manifest, and to single out the proper control strategy in different situations.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.17-30
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• 2002

Incident duration prediction is one of the most important steps of the overall incident management process. An accurate and reliable estimate of the incident duration can be the main difference between an effective incident management operation and an unacceptable one since, without the knowledge of such time durations, traffic impact can not be estimated or calculated. This research presents several multiple linear regression models for incident duration prediction using data consisting of 384 incident cases. The main source of various incident cases was the Traffic Incident Reports filled out by the Motorist Assistant Units of the Korea Highway Corporation. The models were proposed separately according to the time of day(daytime vs. nighttime) and the fatality/injury incurred (fatality/injury vs. property damage only). Two models using an integrated dataset, one with an intercept and the other without it, were also calibrated and proposed for the generality of model application. Some findings are as follows ; ?Variables such as vehicle turnover, load spills, the number of heavy vehicles involved and the number of blocked lanes were found to significantly affect incident duration times. ?Models, however, tend to overestimate the duration times when a dummy variable, load spill, is used. It was simply because several of load spill incidents had excessively long clearance times. The precision was improved when load spills were further categorized into "small spills" and "large spills" based on the size of vehicles involved. ?Variables such as the number of vehicles involved and the number of blocked lanes found not significant when a regression model was calibrated with an intercept. whereas excluding the intercept from the model structure signifies those variables in a statistical sense.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.145-152
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• 2002

Real-time queueing information and/or predictive queue built-up information can be a good criterion in selecting travel options, such as routes, both for users, and for operators in operating transportation system. Provided properly, it will be a key information for reducing traffic congestion. Also, it helps drivers be able to select optimal roues and operators be able to manage the system effectively as a whole. To produce the predictive queue information, this paper proposes a predictive model for estimating and predicting queue lengths, mainly based on Kalman Filter. It has a structure of having state space model for predicting queue length which is set as observational variable. It has been applied for the Namsan first tunnel and the application results indicate that the model is quite reasonable in its efficacy and can be applicable for various ATIS system architecture. Some limitations and future research agenda have also been discussed.

• Journal of Korean Society of Transportation
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• v.21 no.5
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• pp.83-95
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• 2003

This study aims to develop travel time estimation and prediction models on the freeway using measurements from vehicle detectors. In this study, we established a travel time estimation model using traffic volume which is a principle factor of traffic flow changes by reviewing existing travel time estimation techniques. As a result of goodness of fit test. in the normal traffic condition over 70km/h, RMSEP(Root Mean Square Error Proportion) from travel speed is lower than the proposed model, but the proposed model produce more reliable travel times than the other one in the congestion. Therefore in cases of congestion the model uses the method of calculating the delay time from excess link volumes from the in- and outflow and the vehicle speeds from detectors in the traffic situation at a speed of over 70km/h. We also conducted short term prediction of Kalman Filtering to forecast traffic condition and more accurate travel times using statistical model The results of evaluation showed that the lag time occurred between predicted travel time and estimated travel time but the RMSEP values of predicted travel time to observations are as 1ow as that of estimation.

• Journal of Urban Science
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• v.7 no.1
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• pp.45-54
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• 2018

The purpose of this study is to find the factors that reduce prediction error in traffic volume using highway traffic volume data. The ARIMA model was used to predict the day, and it was confirmed that weekday and weekly characteristics were distinguished by prediction error. The forecasting results showed that weekday characteristics were prominent on Tuesdays, Wednesdays, and Thursdays, and forecast errors including MAPE and MAE on Sunday were about 15% points and about 10 points higher than weekday characteristics. Also, on Friday, the forecast error was high on weekdays, similar to Sunday's forecast error, unlike Tuesday, Wednesday, and Thursday, which had weekday characteristics. Therefore, when forecasting the time series belonging to Friday, it should be regarded as a weekly characteristic having characteristics similar to weekend rather than considering as weekday.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.21-36
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• 2015

These days Automated Vehicle(AV) has been receiving attention as a fundamental solution to resolve the various transportation problems and various researches related to the benefits of AV have been done. However, previous researches mainly analyzed the effects in the virtual network. The purpose of this research is to predict and to find out the benefits by introducing the Automated Vehicle to present road traffic system. Thus, the study analyzes the traffic-flow changes of Gyeongbu freeway Seoul-Singal basic section which is planned for setting the test-bed. The results show that Automated Vehicle can have negative effects on the traffic-flow in low volume of LOS A and B. However, the average speed increases and the traffic density decreases in more than LOS C, the traffic volume increase. Therefore, the introduction of Automated Vehicle achieves positive effect on various transportation problems such as the traffic congestion.

• International Journal of Highway Engineering
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• v.9 no.4
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• pp.129-134
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• 2007

In general, based on traffic data in a ideal traffic condition, BPR cost function is used to a variety of transportation policies. However, Some researchers have reported that BRP cost function is not appropriate for analyzing traffic pattern as well as forecasting future demand.(Spiess, 1989 ; Singh, 1999) Therefore, in this paper to solve this problem, a methodology based on data through Micro traffic Simulator Based(MSB) is developed. As a result following outputs are obtained ; (1) presenting a methodology to develop a travel cost function through VISSIM in order to assess transportation policies and (2) developing BRP cost function and MSB cost function from data analysis through VISSIM and verifying availability of MSB function by comparative analysis.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.141-148
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• 2009

An inappropriate evaluation of capacity leads to the incorrect and impractical result due to the transfer of error to the analysis and the evaluation on highway system. The traffic accident which reduces the capacity of road temporarily generates unpredictable congestion, causing difficulties in congestion management. Therefore, this research aims on the measurement of the capacity of the road in accordance to the speed at the accident which is a basic factor when performing analysis. Based on the given approach, the behavior of a vehicle in highway is understood to develop model of critical gap and model of maximum flow rate with respect to the speed of traffic flow. With the established model, the reduction rate of the capacity in highway system at the accident is measured. The result shows that the capacity is reduced by 37% when the speed of the traffic flow is 40km/h. Although the developed model can't be verified clearly, this research has shown that the reduction rate of the capacity in road system has a close relation to the speed.

• Journal of Korean Society of Transportation
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• v.16 no.2
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• pp.145-155
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• 1998

대도시 가로망의 대부분은 신호교차로와 신호교차로가 연결되는 가로(link)로 구성되어 있어 가로의 통행시간은 가로의 주변여건, 차량간의 상호작용 및 교통신호등과 같은 요소에 영향을 받게된다. 따라서 본 연구의 목적은 대도시 가로망에서 신호 연동체계로 운영되는 가로의 통행시간을 예측할 수 있는 모형을 개발하는데 있다. 본 연구는 대구광역시 가로망을 대상으로 연동가로의 교통흐름을 가장 잘 나타내는 Greenberg모형을 이용하여 연동가로의 통행시간 모형을 도출하였다. 도출된 연동가로의 통행시간 모형은 임계통행시간$(t_m$)과 교통량 대가로최대교통량비$(q/q_m)$의 함수로 이루어졌다. $t_m$모형은 안정류상태의 통행시간 및 불안정류상태의 통행시간의 비를 이용하여 개발하였고 가로 용량모형은 상류부와 하류부의 신호조건에 따른 변수와 가로길이를 변수로 하는 모형을 개발하였다. 개발된 모형은 대구광역시를 대상으로 조사한 12개의 연동가로의 자료를 적용하여 연동으로 운영되는 가로의 통행시간 모형을 도출하였다. 도출된 통행시간 모형은 도로용량에 제시한 모형에 비하여 간단하게 가로의 통행시간을 추정할 수 있으며 교통계획에 적용되는 통행시간모형 비하여 가로의 신호 및 운영조건을 포함한 세부적인 통행시간 모형이다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.1
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• pp.1-10
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• 1989

The stress history of a bridge is different depending on the characteristic of traffic flow. Because the flow is varied with vehicle type, weight and headway time etc., statistical analysis in bridges is necessary to estimate the history by traffic flow. By applying the statistical analyses in fracture mechanics, the remaining service life of the structure can be estimated. In this paper, 1)the statistical analysis of vehicle type, weight and headway time etc. to analysis randomness of traffic flow, 2)measuring and analysis of stress history of a real bridge, 3)reappearance of stress history by Monte-Carlo Simulation using constitution ratio of vehicle type, weight and headway time as probabilitic variable, 4)comparision of the calculated and modelled stress history, 5)calculation of reduction factor, 6)comparision of frequency of stress range depending on span length etc. were performed. From the results, the basic modelled stress history which is necessary for the method of estimation of the remaining service life of the structure could be suggested.