• ETRI Journal
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• v.44 no.2
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• pp.194-207
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• 2022

In the last decade, substantial progress has been achieved in intelligent traffic control technologies to overcome consistent difficulties of traffic congestion and its adverse effect on smart cities. Edge computing is one such advanced progress facilitating real-time data transmission among vehicles and roadside units to mitigate congestion. An edge computing-based deep reinforcement learning system is demonstrated in this study that appropriately designs a multiobjective reward function for optimizing different objectives. The system seeks to overcome the challenge of evaluating actions with a simple numerical reward. The selection of reward functions has a significant impact on agents' ability to acquire the ideal behavior for managing multiple traffic signals in a large-scale road network. To ascertain effective reward functions, the agent is trained withusing the proximal policy optimization method in several deep neural network models, including the state-of-the-art transformer network. The system is verified using both hypothetical scenarios and real-world traffic maps. The comprehensive simulation outcomes demonstrate the potency of the suggested reward functions.

• Journal of Korean Port Research
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• v.13 no.1
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• pp.101-112
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• 1999

Traffic accidents increase with the increase of the vehicles in operation on the street. Especially big traffic accidents composed of over 3 killed or 20 injured accidents with the property damage become one of the serious problems to be solved in most of the cities. The purpose of this study is to build the discrimination model on big traffic accidents using the Quantification II theory for establishing the countermeasures to reduce the big traffic accidents. The results are summarized as follows. 1)The existing traffic accident related model could not explain the phenomena of the current traffic accident appropriately. 2) Based on the big traffic accident types vehicle-vehicle, vehicle-alone, vehicle-pedestrian and vehicle-train accident rates 73%, 20.5% 5.6% and two cases respectively. Based on the law violation types safety driving non-fulfillment center line invasion excess speed and signal disobedience were 48.8%, 38.1% 2.8% and 2.8% respectively. 3) Based on the law violation types major factors in big traffic accidents were road and environment, human, and vehicle in order. Those factors were vehicle, road and environment, and human in order based on types of injured driver’s death. 4) Based on the law violation types total hitting and correlation rates of the model were 53.57% and 0.97853. Based on the types of injured driver’s death total hitting and correlation rates of the model were also 71.4% and 0.59583.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.1030-1038
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• 2008

Traffic monitoring method is mainly loop detector and piezo sensor. But this method is only detecting the number of vehicle. Monitoring traffic volume is not checking the number of vehicle but checking the length of access road, width of road, number of passing people, passing vehicle, delayed vehicle. The traffic signal control cycle is not fixed by only passing vehicle number but all related traffic proposal. This paper proposed selecting common characteristic out of each unrelated traffic proposal through Analytic Hierachy Process and this characteristic is applied to compose fuzzy sensor algorithm which find out new traffic volume concept of confusion degree. The accumulated delayed vehicle time is shorter in new fuzzy sensor algorithm applied by AHP than other traffic method

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.276-285
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• 2008

Traffic monitoring method is mainly loop detector and piezo sensor. But this method is only detecting the number of vehicle. Monitoring traffic volume is not checking the number of vehicle but checking the length of access road, width of road, number of passing people,passing vehicle,delayed vehicle. The traffic signal control cycle is not fixed by only passing vehicle number but all related traffic proposal. This paper proposed selecting common characteristic out of each unrelated traffic proposal through Analytic Hierachy Process and this characteristic is applied to compose fuzzy sensor algorithm which find out new traffic volume concept of confusion degree. The accumulated delayed vehicle time is shorter in new fuzzy sensor algorithm applied by AHP than other traffic method

• Journal of Korean Society of Transportation
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• v.19 no.3
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• pp.7-18
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• 2001

The pedestrian signal systems operating presently could provide more time for the pedestrian to cross the street than the previous system, but it would increase the cycle length and cause longer delays at the signalized intersections. For instance, more than 80% of traffic signals would have to have the cycle length increased by 10sec in Daegu Metropolitan areas. Therefore. the purpose of this study is to propose a pedestrian traffic signal time that not only maintains the safety of the pedestrian but also reduces the traffic cycle length. The proposed pedestrian signal time is set to enable enough time for the elderly to cross and the flashing time is set low enough to deter the ordinary person. This new pedestrian signal time can reduce the traffic cycle length at intersections and prevent the Pedestrian crossing during flashing time. In addition to the flashing green should be changed to flashing red to warn the pedestrian he should not begin crossing as opposed to the flashing green which suggest he could cross. In this study, the speed of 1.1m/sec and 0.85m/sec are applied to the new proposed signal time for normal and elderly person respectively after analyzing data collected at Daegu Metropolitan area.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.41-52
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• 2003

The purpose of this study was to test the effects of the pedestrian green signal adjustment on clearance of the turning vehicles impeding the through traffic flow at the signalized intersections, and thereby, suggest some operational criteria for adjustment of the pedestrian green signal. In order to test such effects, the pedestrian green time was adjusted so that it could started a few seconds later than the vehicle green time during peak hours, and thereby, the turning vehicle volume not cleared at the intersection was measured by extending the time gap by 2 seconds. (In general, the pedestrian green signal turns on at the same time as the vehicle green signal.) The results of this test can be summed up as follows; first, the longer the time gap was, the turning vehicle volume not cleared from the intersection decreased more. Second, in case there existed a storage space between intersection and crosswalk the effect of the turning vehicles on the through traffic flows was minimal. Third, at the pelican, the effect of the turning vehicles on the through traffic flow was minimal due to the structure of the intersection and the phase sequence. In conclusion, it was found that the adjustment of pedestrian green signal had the effect of enhancing the intersection operation. When adjusting the pedestrian green signal, it was deemed necessary to thoroughly survey the geometric structure of the intersection and collect the data on the turning traffic volume and thereby, apply the results of analysis flexibly to each intersection.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.6-13
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• 2002

In this paper, we propose an image processing based method to measure red-time and green-time backward moving shockwave speed automatically at signalized intersections. Shockwave means the discontinuous boundary line between different vehicle traffic flows, and its moving speed is called shockwave speed which is obtain from the slope of boundary line. In this paper, we compose distance-time diagram for measuring shockwave speed automatically. By global vehicle tracking, we draw all of the vehicle moving path on distance-time diagram. We analyze the slope change pattern of curved moving path line, and compute red-time and green-time backward moving shockwave speed. We obtain the measurement result of shockwave speed, when applying above mentioned proposed method to experiment at signalized intersections, Once we can measure the shockwave speed, we could apply the result to highway ramp metering and automatic signal control at intersections effectively since we know the situation of frontal congestion easily.

• Journal of Korean Society of Transportation
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• v.19 no.3
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• pp.75-88
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• 2001

Signal optimization model for alternative use of lanes at a signalized intersection with an stop-line added backward was presented in this paper. The simulation results shot-ed that the traffic fed from the stop-line passed the intersection in each specified phasing interval for left and through traffic. The experimental results indicated that the proposed model was much superior to traditional signal optimization methodology in reducing delay, fuel consumption, and disutility index for delay and stops. The effects for reducing delay were greater than those for doing fuel consumption and disutility index due to the added stop-line. The proposed model is expected to alleviate traffic congestion at intersections, both which have no left turn pocket, and which have large left turn volume. The model is recommended to adapted for intersections spaced long among them with no near driveway.

• Journal of the Korean Society for Railway
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• v.18 no.1
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• pp.25-32
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• 2015

It has been subject to question whether a conventional traffic signal controller can support efficient operation at grade intersections in which vehicles and tram lines cross concurrently. This study proposes a list of functional requirements for a traffic signal controller to support effective operation of trams at such an intersection. The considered details includes the combinations of geometric conditions at which vehicle, bus, and tram lines are aligned, the types of exclusive tram signals, and the combinations of various signal phases, including exclusive tram phases, which are currently undefined in the nation. The results suggest that the controller should be capable of dealing with the NEMA standard overlap relays and a quadruple-ring phase representation scheme.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.113-129
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• 2021

Recently, traffic congestion in the city is continuously increasing due to the expansion of the living area centered in the metropolitan area and the concentration of population in large cities. New road construction has become impossible due to the increase in land prices in downtown areas and limited sites, and the importance of efficient data-based road operation is increasingly emerging. For efficient road operation, it is essential to classify appropriate scenarios according to changes in traffic conditions and to operate optimal signals for each scenario. In this study, the Dynamic Time Warping model for cluster analysis of time series data was applied to traffic volume and speed data collected at continuous intersections for optimal scenario classification. We propose a methodology for composing an optimal signal operation scenario by analyzing the characteristics of the scenarios for each data used for classification.