• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.25-37
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• 2020

As social costs of traffic congestion increase, various studies are underway to predict road speed. In order to improve the accuracy of road speed prediction, unexpected traffic situations need to be considered. In this paper, we propose a road speed prediction scheme considering traffic incidents affecting road speed. We use not only the speed data of the target road but also the speed data of the connected roads to reflect the impact of the connected roads. We also analyze the amount of speed change to predict the traffic congestion caused by traffic incidents. We use the speed data of connected roads and target road with input data to predict road speed in the first place. To reduce the prediction error caused by breaking the regular road flow due to traffic incidents, we predict the final road speed by applying event weights. It is shown through various performance evaluations that the proposed method outperforms the existing methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5135-5142
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• 2011

A flexible mechanism is proposed in this paper to improve the dynamic response performance of a traffic flow control system in an urban area. The roads, vehicles, and traffic control systems are all modeled as intelligent systems, wherein a wireless communication network is used as the medium of communication between the vehicles and the roads. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads, based on all the information from the vehicles and the roads. This improves the flexibility of traffic flow and offers a much more efficient use of the roads over a traditional traffic control system. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm, and simulation results showed that the proposed mechanism can improve the traffic efficiency and the waiting time at the signal light by more than 30% in various conditions compare to the traditional signaling system.

• Proceedings of The KACE
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• 2018.01a
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• pp.129-132
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• 2018

교통 체증은 차량 이용이 대중화된 지금 많은 문제를 야기하고 있다. 교통 정체로 인한 시간 허비, 장시간 운전으로 인한 운전자의 피로 증가, 매연 배출로 인한 환경 오염 촉진 등 교통 체증은 사회적으로 무시할 수 없는 여러 문제들을 불러온다. 이에 본 연구는 신호 체계 개선에 초점을 두어 유전 알고리즘을 이용한 도시 규모의 유동성 연동 신호 체계를 구현하고자 하였다. 이를 위하여 교통 시뮬레이션 프로그램 SUMO를 이용하여 실험 환경을 조성하고, 4개의 사거리와 16개의 사거리, 그리고 선릉역 인근의 실제 도로망에서의 최적 신호 주기를 탐색하였다. 실험 결과 4개의 사거리의 경우 유전 알고리즘 적용 전의 초기 설정에 비해 자동차들의 평균 이동 시간이 31.1% 감소, 16개의 사거리의 경우 6.2% 감소, 실제 도로에서는 1.1% 감소함을 확인할 수 있었다. 따라서 유전 알고리즘을 이용한 새로운 교통 체계는 교통 정체를 완화하는 효과가 있으며 본 연구를 실제에 적용한다면 도시 규모의 도로망에서 시간대 별로 교통 흐름을 최적화하는 맞춤형 신호 주기를 구할 수 있을 것이다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.44-57
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• 2019

Various studies have been conducted to solve traffic congestions in many metropolitan cities through accurate traffic flow prediction. Most studies are based on the assumption that past traffic patterns repeat in the future. Models based on such an assumption fall short in case irregular traffic patterns abruptly occur. Instead, the approaches such as predicting traffic pattern through big data analytics and artificial intelligence have emerged. Specifically, deep learning algorithms such as RNN have been prevalent for tackling the problems of predicting temporal traffic flow as a time series. However, these algorithms do not perform well in terms of long-term prediction. In this paper, we take into account various external factors that may affect the traffic flows. We model the correlation between the multi-dimensional context information with temporal traffic speed pattern using deep neural networks. Our model trained with the traffic data from TOPIS system by Seoul, Korea can predict traffic speed on a specific date with the accuracy reaching nearly 90%. We expect that the accuracy can be improved further by taking into account additional factors such as accidents and constructions for the prediction.

• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.285-294
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• 1998

기존 도로시설을 최대로 이용하고 교통의 흐름을 질적으로 향상시키기 위해서는 과포화 상태를 고려한 교통시설운영방법을 개선할 필요가 있다. 속도-교통량관계는 교통시설운영의 평가와 서비스수준 산정을 위한 주요 판단기준이 된다. 본 논문에서는 경부고속도로 종점부 구간의 현장조사를 통해 과포화상태의 속도-교통량 관계를 조사 분석하였고 그 결과 다음 몇 가지 결론을 얻을 수 있었다. 첫째, 한국도로용량편람을 비롯한 우리 나라 연구결과는 일반적으로 50km/hr 일 때 용량상태가 나타난다고 알려져 있으나 본 조사결과에 의하면 약 85km/hr 정도에서 용량상태가 발생함을 관측할 수 있었다. 둘째, 과포화구간에서 속도에 따른 통과교통량 증감추이는 대기행렬 증가시 급격한 속도-교통량의 감소가 있는 반면에 대기행렬해소시 속도-교통량의 증가는 완만하게 회복됨을 보였다. 셋째, Ontario 고속도로의 경우와 본 조사연구결과는 비교해본 결과 과포화시 한국의 경우 미국과 동일한 통행속도에서 더 많은 교통량이 통행하는 것으로 확인되었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.582-585
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• 2018

As traffic volume increases and road networks become more complicated, identifying for accurate traffic flow and driving smooth traffic flow are a concern of many countries. There are various analytical techniques and studies which desire to study about effective traffic flow. However, the necessary activity is finding the traffic flow pattern through data visualization including location information. In this paper aim to study a real-world urban traffic trajectory and visualize a pattern of traffic flow with a simulation tool. Our experiment is installing the sensor module in 40 taxis and our dataset is generated along 24 hours and unscheduled routes. After pre-processing data, we improved an open source traffic visualize tools to suitable for our experiment. Then we simulate our vehicle trajectory data with a dots animation over a period of time, which allows clearly view a traffic flow simulation and a understand the direction of movement of the vehicle or route pattern. In addition we further propose some novel timelines to show spatial-temporal features to improve an urban environment due to the traffic flow.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1179-1190
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• 2010

Management of the existing traffic network and understanding current traffic conditions is the most important and effective way to solve traffic congestion. This research investigates the status of Korea expressway through the Speed-Flow-Density diagram and finds the best suitable queueing model for each area. Dynamic structure in the queueing model enables us to reflect the structural change of the road in case of traffic congestion. To find the best model and estimate the parameters, we use the Newton-Raphson method. Finally, we examine the road efficiency in view of the optimal speed and density using the conditional distribution of speed and density of a S-F-D diagram.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.1
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• pp.59-77
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• 2008

The purpose of this study is to investigate the impact of traffic-related air pollution on the urban population in the Metropolitan Seoul area. In particular, this study analyzes urban population exposure to traffic-related particulate materials(PM). For the purpose, this study examines the relationships between traffic flows and PM concentration levels during the last fifteen years. Traffic volumes have been decreased significantly in recent year in Seoul, however, PM levels have been declined less compare to traffic volumes. It may be related with the rapid growth in the population and vehicle numbers in Gyenggi, the outskirt of Seoul, where several New Towns have been developed in the middle of 1990's. The spatial pattern of commuting has changed, and thus and travel distances and traffic volumes have increased along the main roads connecting CBDs in Seoul and New Towns consisting of large residential apartment complexes. These changes in traffic flows and travel behaviors cause increasing exposure to traffic-related air pollution for urban population over the Metropolitan Seoul area. GIS techniques are applied to analyze the spatial patterns of traffic flows, population distributions, PM distributions, and passenger flows comprehensively. This study also analyzes real time base traffic flow data and passenger flow data obtained from T-card transaction database applying data mining techniques. This study also attempts to develop a space-time model for assessing journey-time exposure to traffic related air pollutants based on travel passenger frequency distribution function. The results of this study can be used for the implications for sustainable transport systems, public health and transportation policy by reducing urban air pollution and road traffics in the Metropolitan Seoul area.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.440-443
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• 2000

오늘날 도시교통은 계속적으로 증가하는 자동차에 의해 극심한 정체를 겪고 있다. 복잡한 교통상황에서 도시의 한정된 도로를 최적으로 이용함으로써 교통의 흐름을 효율적으로 통제할 수 있는 시스템의 필요성이 높아지고 있다. 멀티 에이전트 시스템은 이러한 복잡한 교통 상황을 해소하는 새로운 방법으로 인식되고 있다. 본 논문에서는 Visual C++ 언어를 이용하여 개발하고 교차로망 시뮬레이션을 위한 에이전트 기반의 퍼지 논리 제어기를 제안하였다. 제안된 퍼지 논리 제어기는 교통량이 많더라도 교통신호 주기를 통제하기에 적합한 방법이며, 이 방법의 효과를 교차로망 시뮬레이션을 이용하여 입증하였다.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.190-201
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• 2021

The variable message sign (VMS) is equipment to improve the efficiency of traffic flow and safety of travel by providing real-time information to road users on traffic, road, weather situation, and traffic control due to construction. The information messages of the letter-based VMS taking up most of the VMS on the general national highways consist of section, travel time in sections, and road control situation. This study devised an improvement plan centered on road users, not road managers-centered existing message-based VMS through an analysis of road users' preference targeting the letter-based VMS operated in the general national highways in the Seoul Metropolitan Area. By presenting the measure for system improvement through which information on unexpected situations that road users prefer the most can be quickly and efficiently provided, this study aims to improve the efficiency of road user-centered VMS traffic information.