• Proceedings of the Korea Air Pollution Research Association Conference
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• 2003.11a
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• pp.378-379
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• 2003

도로에서의 비산먼지는 건설현장 트럭에 의한 토사의 유입, 운반 중에 날리는 토사, 토양의 침식, 겨울철 모래살포, 타이어의 마모등에 의하여 도로표면에 쌓인 먼지가 차량의 운행이나 바람으로 인하여 발생한다 국내 주요도시 및 산업단지는 대부분이 포장도로로서 주변환경에서 유입되는 먼지와 함께 차량의 운행으로 인한 비산먼지(Fugitive dust)의 영향이 지대하며, 건설현장에서 발생되는 비산먼지와 함께 도시ㆍ산단지역의 미세먼지 배출량에 큰 기여를 하는 것으로 조사되었다. (중략)

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2002.11a
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• pp.312-313
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• 2002

도로에서의 비산먼지는 건설현장 트럭에 의한 토사의 유입, 운반 중에 날리는 토사, 토양의 침식, 겨울철 모래살포, 타이어의 마모 등에 의하여 도로표면에 쌓인 먼지가 차량의 운행이나 바람으로 인하여 발생한다. 국내 주요도시 및 산업단지는 대부분이 포장도로로서 주변환경에서 유입되는 먼지와 함께 차량의 운행으로 인한 비산먼지(Fugitive dust)의 영향이 지대하며, 건설현장에서 발생되는 비산먼지와 함께 도시·산단지역의 미세먼지 배출량에 큰 기여를 하는 것으로 조사되었다. (중략)

• Journal of Korean Society of Transportation
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• v.21 no.5
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• pp.19-29
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• 2003

The purpose of this study is to analyse the effect of the parking information on the waiting time using the simulation method. Stated Preference survey has been implemented to construct the parking lot choice model. A queue simulation is carried out to investigate the effect of various parking information on the waiting time. The results show that providing parking information is likely to increase the utilization of parking place and to decease the waiting time of individual vehicle. Furthermore, as the parking demand increases, the detailed and quantitative parking information such as "5 minutes delay" is more effective than qualitative parking information such as "available".

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.39-57
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• 2018

The purpose of this study was to construct an artificial intelligence model that learns and estimates the relationship between vehicle queue length and link travel time in urban areas. The vehicle queue length estimation model is modeled by three models. First of all, classify whether vehicle queue is a link overflow and estimate the vehicle queue length in the link overflow and non-overflow situations. Deep learning model is implemented as Tensorflow. All models are based DNN structure, and network structure which shows minimum error after learning and testing is selected by diversifying hidden layer and node number. The accuracy of the vehicle queue link overflow classification model was 98%, and the error of the vehicle queue estimation model in case of non-overflow and overflow situation was less than 15% and less than 5%, respectively. The average error per link was about 12%. Compared with the detecting data-based method, the error was reduced by about 39%.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.163-169
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• 1997

본 논문에서는 평균 차량속도를 향상시키고 평균 차량대기시간을 줄이는 새로운 최적 교통신호주기산출방법을 제안한다. 전자교통신호등은 차량은 교차로에 많을때에는 교통신호주기을 연장 할 수 있고 교차로에 차량이 적을 경우에는 교통신호주기를 단축할 수 있다. 그러나 요즈음과 같이 교통체증이 많아서 평균주행속도가 10km - 20km 로 서행우전할 수 밖에 없을때에는 전자신호등의 기능을 수행할 수 없다. 그러므로 본 논문에서는 승용차대기시간을 단축하기위해서 최적 경로 알고리즘을 사용하여 목적지까지 가장 빠르게 도착할 수 있는 교통신호설계 소프트웨어 Tool을 개발하였다. 컴퓨터 모의실험결과 G.P.S.를 자동차에 내장하여 최단경로선택을 하는 차량이 기존의 최적경로선택기능이 없는 차량보다 승용타대기시간 및 평균주행속도가 10% - 32% 가량 개선시킬 수 있음을 입증하였다.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.19-24
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• 2010

The number of automobiles are continuously increasing in Korea since 1990's and it causes frustrating commuting traffic and holyday traffic. Meanwhile, the obsolete traffic signal control system is still under static control based on the aggregated traffic statistics thus it is not sufficiently adaptive in real world traffic situation that changes in real time. Thus, in this paper, we propose an adaptive signal control system using fuzzy control technology that can react to real time traffic situations. The method computes the priority of signal phases based on the number of waiting automobiles and occupying time on intersection using fuzzy membership functions. The phase with highest priority obtains "proceed" signal. Also, the duration of this "proceed" signal is determined based on the ratio of number of waiting automobiles of given phase and total number of waiting automobiles on intersection. In experiment, we show that the proposed fuzzy control system is better than the static control system for all sorts of traffic congestion situations by simulation.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.181-190
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• 2022

In this paper, we use a LiDAR sensor and an image camera to detect a left-turning waiting vehicle in two ways, unlike the existing image-type or loop-type left-turn detection system, and a left-turn traffic signal corresponding to the waiting length of the left-turning lane. A system that can efficiently assign a system is introduced. For the LiDAR signal transmitted and received by the LiDAR sensor, the left-turn waiting vehicle is detected in real time, and the image by the video camera is analyzed in real time or at regular intervals, thereby reducing unnecessary computational processing and enabling real-time sensitive processing. As a result of performing a performance test for 5 hours every day for one week with an intersection simulation using an actual signal processor, a detection rate of 99.9%, which was improved by 3% to 5% compared to the existing method, was recorded. The advantage is that 99.9% of vehicles waiting to turn left are detected by the LiDAR sensor, and even if an intentional omission of detection occurs, an immediate response is possible through self-correction using the video, so the excessive waiting time of vehicles waiting to turn left is controlled by all lanes in the intersection. was able to guide the flow of traffic smoothly. In addition, when applied to an intersection in the outskirts of which left-turning vehicles are rare, service reliability and efficiency can be improved by reducing unnecessary signal costs.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.5
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• pp.42-53
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• 2016

This study aims to evaluate the performance of Hook-turn operation with various sizes of bicycle waiting zone(WZ) and to determine the optimal size of bicycle WZ under various traffic and control circumstances. An extensive simulation study was performed to examine bicycle and vehicle delay trends for given experimental design. Results showed that vehicle delay was insensitive to the size of waiting zone, but bicycle delay was reduced as the size of waiting zone increased in general. The delay performance indicated a similar trend between with RTOR and without RTOR operation, but vehicle delay slightly increased and bicycle delay slightly decreased without RTOR. Regarding to optimal waiting zone size, 6 WZ was recommended for general conditions with RTOR, but 9 WZ was recommended when bicycle left-turn volume was greater than 120 v/h. 6 WZ was recommended for general conditions without RTOR, but 12 WZ was recommended when bicycle left-turn volume was greater than 90 v/h.

• 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.

• Korean Journal of Construction Engineering and Management
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• v.24 no.1
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• pp.21-30
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• 2023

Excessive complaints and traffic jams occurred as customers who visited the Drive-thru waited in a long line. Company S recommends DT Pass to reduce the queues. Therefore, this study confirmed the improvement in performance of the queue increasing the number of stores operated by two servers insteaol of one using a queue model. And then confirmed performance improvement by dividing them into DT and DT Pass. After that, the L value derived through the queue model and the number of queues in each store were compared to calculate the number of queues to be additionally provided. Through this, the validity of selecting the minimum number of queues in the future is verified based on the results derived in this study.