• 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.22 no.3 s.74
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• pp.85-94
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• 2004

Loop detection systems have been used in real-time signal control system to collect traffic information for estimating queue lengths. The queue length algorithm uses speed as a key variable estimated from occupancy time and average vehicle length. The measurement of average vehicle length is affected from the lengths of feeder cable, but their effects have not yet been evaluated. In this study, the variability of average vehicle length due to the lengths of feeder cable is assessed through a field study, and a practical guidelines is proposed. By applying this result, the operational performance of real-time signal control system could be improved.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.145-151
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• 2009

Current highway design standards is based on the safety under the free flow condition. The length of deceleration lane is also determined in terms of the deceleration distance which is necessary for the driers to adjust the vehicle speed from the speed limit on the main road to that on the exit ramp of the interchange. However, the queues are frequently developed on the deceleration, and the following vehicles to exit must decelerate on the main road. It may cause delay on the main road and traffic accidents. This study is to suggest a methodology to minimize such problems with the shock-wave theory. The queue length of exiting vehicles can be estimated by the design speeds, traffic volumes of main road and the exiting ramp, and the countermeasures to the operational problems. According to the results, the queue length can be shortened to 80% by upgrading the design speed of exit ramp as the amount of 10km/h. Fifty percent of queue length can be shortened by adding an additional lane on the ramp to two lanes.

• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.59-88
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• 1996

This study has determined optimal type, and location of loop detector to measure accurately traffic condition influenced by traffic variation with real time. Optimal type of loop detector for through vehicle at stop bar was determined by confidences of occupancy period, and nonoccupancy period, and so appropriate detector type for application to real time traffic control system has been decided on special loop detector.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.75-85
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• 2000

The Purpose of this study is to analyze wether the composition of training sample have a relation with the Predictive ability and the learning results of ANNs(Artificial Neural Networks) fur predicting one cycle ahead of the queue length(veh.) in a signalized intersection. In this study, ANNs\` training sample is classified into the assumption of two cases. The first is to utilize time-series(Per cycle) data of queue length which would be detected by one detector (loop or video) The second is to use time-space correlated data(such as: a upstream feed-in flow, a link travel time, a approach maximum stationary queue length, a departure volume) which would be detected by a integrative vehicle detection systems (loop detector, video detector, RFIDs) which would be installed between the upstream node(intersection) and downstream node. The major findings from this paper is In Daechi Intersection(GangNamGu, Seoul), in the case of ANNs\` training sample constructed by time-space correlated data between the upstream node(intersection) and downstream node, the pattern recognition ability of an interrupted traffic flow is better.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.1
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• pp.1-14
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• 2014

The expansion of the physical road in response to changes in social conditions and policy of the country has reached the limit. In order to alleviate congestion on the existing road to reconsider the effectiveness of this method should be asking. Currently, how to collect traffic information for management of the intersection is limited to point detection systems. Intelligent Transport Systems (ITS) was the traffic information collection system of point detection method such as through video and loop detector in the past. However, intelligent transportation systems of the next generation(C-ITS) has evolved rapidly in real time interval detection system of collecting various systems between the pedestrian, road, and car. Therefore, this study is designed to evaluate the development of an algorithm for queue length based real-time traffic signal control methodology. Four coordinates estimate on time-space diagram using the travel time each individual vehicle collected via the interval detector. Using the coordinate value estimated during the cycle for estimating the velocity of the shock wave the queue is created. Using the queue length is estimated, and determine the signal timing the total queue length is minimized at intersection. Therefore, in this study, it was confirmed that the calculation of the signal timing of the intersection queue is minimized.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.1 s.4
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• pp.85-96
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• 2004

The study begin with a basic concept, if the occupancy length of vehicle detector is directly proportional to the delay of vehicle. That is, it analogize vehicle's delay of a occupancy time. The results of a study was far superior in the estimation of a queue length. It is a very good points the operator is not necessary to optimize s1, s2, Thdoc. Thdoc(critical congestion degree) replaced 0.7 with 0.2 - 0.3. But, if vehicles have been experience in delay was not occupy vehicle detector, the study is in existence some problems. In conclusion, it is necessary that stretch queue detector or install paired queue detector. Also I want to be made steady progress a following study relation to this study, because it is required traffic signal control on congestion.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.161-165
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• 2005

In order to produce an optimal traffic cycle. We must first check how many waiting cars are at the lower intersection, because waiting queue is bigger than the length of upper traffic intersection. Start up delay time and vehicle waiting time occurs. To reduce vehicle waiting time, in this paper, we present an optimal green time algorithm using fuzzy neural network. Through computer simulation has been proven to be improved average vehicle speed than fixed traffic signal light which do not consider different intersection conditions.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.107-116
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• 2005

The information on travel time in providing the information of traffic to drivers is one of the most important data to control a traffic congestion efficiently. Especially, this information is the major element of route choice of drivers, and based on the premise that it has the high degree of confidence in real situation. This study developed a vehicle arrival time prediction algorithm called as "VAT-DV" for 6 corridors in total 6.1Km of "Nam-san area trffic information system" in order to give an information of congestion to drivers using VMS, ARS, and WEB. The spatial scope of this study is 2.5km~3km sections of each corridor, but there are various situations of traffic flow in a short period because they have signalized intersections in a departure point and an arrival point of each corridor, so they have almost characteristics of interrupted and uninterrupted traffic flow. The algorithm uses the information on a demand volume and a queue length. The demand volume is estimated from density of each points based on the Greenburg model, and the queue length is from the density and speed of each point. In order to settle the variation of the unit time, the result of this algorithm is strategically regulated by importing the AVI(Automatic Vehicle Identification), one of the number plate matching methods. In this study, the AVI travel time information is composed by Hybrid Model in order to use it as the basic parameter to make one travel time in a day using ILD to classify the characteristics of the traffic flow along the queue length. According to the result of this study, in congestion situation, this algorithm has about more than 84% degree of accuracy. Specially, the result of providing the information of "Nam-san area traffic information system" shows that 72.6% of drivers are available.