• Journal of Digital Contents Society
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• v.10 no.2
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• pp.357-365
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• 2009

To effectively exploit the underlying network bandwidth while maximizing user perceivable QoS, mandatory to make proper estimation on packet loss and queuing delay of the underling network. This issue is further emphasized in wireless network environment where network bandwidth is scarce resource. In this work, we focus our effort on developing performance model for wireless network. We collect packet trace from actually wireless network environment. We find that packet count process and bandwidth process in wireless environment exhibits long range property. We extract key performance parameters of the underlying network traffic. We develop an analytical model for buffer overflow probability and waiting time. We obtain the tail probability of the queueing system using Fractional Brown Motion (FBM). We represent average queuing delay from queue length model. Through our study based upon empirical data, it is found that our performance model well represent the physical characteristics of the IEEE 802.11b network traffic.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.671-680
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• 2016

This research suggested a new real-time traffic signal control algorithm using fusion data of the travel time and the occupancy rate. This research applied the travel time data of traffic information system to traffic signal operation, and developed the signal control process using the degree of saturation that was estimated from the travel time data. This algorithm estimates a queue length from the travel time based on a deterministic delay model, and includes the process to change from the queue length to the degree of saturation. In addition, this model can calculate the traffic signal timings using fusion data of the travel time and the occupancy rate based on the saturation degree. The micro simulation analysis was conducted for effectiveness evaluation. We checked that the average delay decreased by up to 27 percent. In addition, we checked that this signal control algorithm could respond to a traffic condition of oversaturation and detector breakdown effectively and usefully. This research has important contribution to apply the traffic information system to traffic signal operation sectors.

• 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.33 no.1
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• pp.1-13
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• 2015

This study aims to develop a mainline metering strategy considering queue imbalance among lanes that can reduce congestion at a toll plaza section by managing queue caused by mainline metering. The suggested strategy considers simultaneously optimizing the number of cars in merging area and managing queue by lane. This study analyzes the effectiveness of the strategy with respect to the average travel time and the occurrence rate of spillback using the PARAMICS. The results show that the suggested strategy has an effect on reducing congestion and improving operation efficiency at toll plaza. In particular, the congestion become more intensified when the length of waiting space is shorter; however, this study shows that the suggested strategy can relieve the congestion in that condition.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.26-36
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• 2021

In this study, a deep learning model for predicting the queue length was developed using the information collected from the image detector. Then, a multiple regression analysis model, a statistical technique, was derived and compared using two indices of mean absolute error(MAE) and root mean square error(RMSE). From the results of multiple regression analysis, time, day of the week, occupancy, and bus traffic were found to be statistically significant variables. Occupancy showed the most strong impact on the queue length among the variables. For the optimal deep learning model, 4 hidden layers and 6 lookback were determined, and MAE and RMSE were 6.34 and 8.99. As a result of evaluating the two models, the MAE of the multiple regression model and the deep learning model were 13.65 and 6.44, respectively, and the RMSE were 19.10 and 9.11, respectively. The deep learning model reduced the MAE by 52.8% and the RMSE by 52.3% compared to the multiple regression model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.95-109
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• 2017

The golden time of emergency vehicle is directly connected to the public safety. Therefore, national attention has increased to cut down the emergency vehicle's travel time. In order to shorten the intial dispatch time of it, emergency preemption system was installed at five intersections, and after test operation, whether it could be introduced in the country was estimated. We analyzed the effect of the traffic volume, emergency vehicle's travel time, and queue length under preemption and non-preemption. In the verification of the emergency preemption system, it was confirmed that the emergency vehicle's travel time was reduced from 350% to 24% compared to non-preemption system(TOD). In the saturated condition, queue length were remained 15 minutes and near saturated condition was about 30 or 45 minutes. At the non-saturated condition, the queue length's difference between emergency preemption system and general signal was small.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.203-213
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• 2008

U-Turn offers convenience to drivers. U-Turn increases efficiency of traffic flow. But Standard of U-Turn is not clear. It caused many problems of traffic flow and traffic safety. This study estimate length between U-Turn location with front intersection based on stopping sight distance and left-turn vehicle's queue length. Variables are used traffic volume and operation speed. This study Analysis of U-Turn vehicle's behaviors and classification of conflict form by investigation. U-Turn length estimating based on relationship analysis between conflict with U-Turn length. Variables are used lane changing angles and operation speed. This study estimates length between U-Turn location with back intersection based on gap acceptance theory. Variables are used traffic volume, operation speed and lane changing angles. So, U-Turn location and length estimated considering traffic flow and traffic safety.

• Journal of Korean Society of Transportation
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• v.19 no.3
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• pp.101-113
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• 2001

Since late 1970s. one of the principal research areas in transportation problem is dynamic traffic assignment (DTA). Although many models have been developed regarding DTA, yet they have some limits of describing real traffic patterns. This reason comes from the fact that DTA model has the time varying constraints such as state equation, flow propagation constraint, first in first out(FIFO) rule and queuing evolution. Thus, DTA model should be designed to satisfy these constraints as well as dynamic route choice condition, dynamic user equilibrium. In this respect, link-based DTA models have difficulty in satisfying such constraints because they have to satisfy the constraints for each link, while path-based DTA models may easily satisfy them. In this paper we develop a path-based DTA model. The model includes point queue theory to describe the queue evolution and simulation loading method for depicting traffic patterns in more detail. From a numerical test, the model shows promising results.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.2 s.5
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• pp.29-40
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• 2004

The performance of the National Highway is raised, but the capacity of the signalized intersection on the National Highway is low. It's operated by TOD(Time Of Day) mode. To evaluate of the performance of COSMOS(Cycle, Offset, Split Model for Seoul), a real time traffic adaptive signal control system, on the National Highway, studied volume, travel time and queuing length at TOD control and TRC(Traffic responsive Control). Consequently, the average travel speed at TRC is high $2.9\~16.7$km/h then the average travel speed at TOD control. And te queuing length at TRC is low $15\~196m$ then the queuing length at TOD control.

• 한국ITS학회:학술대회논문집
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• 2004.11a
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• pp.125-132
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• 2004