• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.522-530
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• 2014

Spatio-temporal congestion evolution pattern can be reproduced using the VDS(Vehicle Detection System) historic speed dataset in the TMC(Traffic Management Center)s. Such dataset provides a pool of spatio-temporally experienced traffic conditions. Traffic flow pattern is known as spatio-temporally recurred, and even non-recurrent congestion caused by incidents has patterns according to the incident conditions. These imply that the information should be useful for traffic prediction and traffic management. Traffic flow predictions are generally performed using black-box approaches such as neural network, genetic algorithm, and etc. Black-box approaches are not designed to provide an explanation of their modeling and reasoning process and not to estimate the benefits and the risks of the implementation of such a solution. TMCs are reluctant to employ the black-box approaches even though there are numerous valuable articles. This research proposes a more readily understandable and intuitively appealing data-driven approach and developes an algorithm for identifying congestion patterns for recurrent and non-recurrent congestion management and information provision.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.377-393
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• 2016

Vehicle emissions have been known as a critical factor to give a negative impact on the public health. In particular, particulate matters(PM) and NOx are highly related with respiratory diseases such as asthma. This study aimed at analyzing spatio-temporal patterns of PM and NOx generated from urban freeway traffic. MOVES, which is a well-known emission analysis tool presented by US Environmental Protection Agency(EPA), was applied to estimate PM and NOx based on traffic volume and speed data obtained from Seoul Outer Ring Expressway during January~June, 2012. K-means clustering analysis was used for categorizing the Level of Vehicle Emissions(LOVE) to support more systematical identification of the significance of emissions. Then, spatio-temporal analyses of estimated emissions were conducted by LOVE. Finally, this study proposed a set of strategies to reduce both PM and NOx to enhance public health based on analysis results.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.4
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• pp.1-11
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• 2014

Traffic congestion cost is more likely to occur in the inner city than interregional road, and it accounts for about 63.39% of the whole. Therefore, it is important to mitigate traffic congestion of the inner city. Traffic congestion in the urban could be divided into Recurrent congestion and Non-recurrent congestion. Quick and accurate detection of Non-recurrent congestion is also important in order to relieve traffic congestion. The existing studies about incident detection have been variously conducted, however it was limited to Uninterrupted Traffic Flow Facilities such as freeway. Moreover study of incident detection on the interrupted Traffic Flow Facilities is still inadequate due to complex geometric structure such as traffic signals and intersections. Therefore, in this study, incident detection model was constructed using by Artificial Neural Network to aim at urban arterial road that is interrupted traffic flow facility. In the result of the reliability assessment, the detection rate were 46.15% and false alarm rate were 25.00%. These results have a meaning as a result of the initial study aimed at interrupted traffic flow. Furthermore, it demonstrates the possibility that Non-recurrent congestion can be detected by using car navigation data such as car navigator system device.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.119-128
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• 2008

Weather like rain, strong wind or snowfall may make the road condition deteriorated and sometimes induce traffic accidents, which lead to severe traffic congestion, thereby travelers may change their destinations elsewhere. Although origin-destination trip information is required to analyze transportation planning in urban area, there are little researches on the relationship between weather condition and travel patterns. This paper investigates the characteristics of travel patterns on expressway in rainy days of 2006. We compare the normal travel patterns with those of rainy days by the travel distance for each vehicle type. Results show that traffic volume and travel distance have been reduced in rainy days as we expect, and also show different travel patterns for weekday and weekend.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.1
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• pp.16-26
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• 2011

Variable speed limit(VSL) is one of the highway ITS techniques designed to prevent accidents and traffic slow down by reducing congestion or speed variation between vehicles and lanes prior to arrive at the accident location by limiting speed. In Korea, while people have recognized the need for variable speed limit beginning with Seoul's urban expressway and installed facilities in order to provide guide for speed limit per lane and lane use, there has not been enough development of algorithm for internal administration as well as research on the basic principles behind administering variable speed limit. This study is for modeling and evaluating the VSL strategies based on the traffic flow theory. Supply-Demand method of the Cell Transmission Model is applied to demonstrate the traffic features and shockwaves to upstream of the bottleneck with/without VSL. We verified the explanation of Cell Transmission Model for the numerical example. and as the result, it is found that VSL strategies can reduce the total travel time in the congested section and variation of the speed. It means VSL is useful to improve the traffic condition and the safety on highway

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.86-99
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• 2021

One of the methods to alleviate traffic congestion is to increase the efficiency of the roads by providing traffic condition information on road user and distributing the traffic. For this, reliability must be guaranteed, and quantitative real-time traffic speed prediction is essential. In this study, and based on analysis of traffic speed related to traffic conditions, historical data correlated with traffic flow were used as input. We developed an LSTM model that predicts speed in response to normal traffic conditions, along with a CNN-LSTM model that predicts speed in response to incidents. Through these models, we try to predict traffic speeds during the hour in five-minute intervals. As a result, predictions had an average error rate of 7.43km/h for normal traffic flows, and an error rate of 7.66km/h for traffic incident flows when there was an incident.

• Journal of Korean Society of Transportation
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• v.20 no.6
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• pp.115-128
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• 2002

Traffic engineers have developed and implemented various microscopic simulation models to verify the traffic performance and to prevent the expected problems. The existing microscopic simulation models categorize drivers into several types to reflect various drivers' driving patterns but miss the dynamics of drivers' behavior changed based upon the traffic conditions. It was found from the field data collected from two different merging sections on an urban freeway in Seoul, Korea, that the drivers' critical gap distributions are changed based on (1) the traffic density on the adjacent lane to the acceleration lane and (2) the opportunities left to merge in terms of distance to the end of acceleration lane. It was also found from the study that the drivers' critical gap distributions follow the Normal distribution. and its mean and variance change while a vehicle progresses on an acceleration lane. This paper proposes a new gap-acceptance model developed based on a set of drivers' critical gap distributions from each segment on the acceleration lanes. Through the comparison study between the field data and the results from the simulation utilizing the proposed model, it was verified that (1) the distribution of merging points on an acceleration lane to the adjacent main lane at different density levels, (2) the size of the gap accepted for merging and (3) the speed difference between the merging vehicle and the trailing vehicle at the time of merging are statistically identical to the field data at 95% confidence level.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.133-146
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• 2021

Providing weather information on roads today means that the road weather conditions near weather observation points are presented to road managers and road users. These weather observation points are managed by the Korea Meteorological Administration. However, it is difficult to provide accurate weather information due to physical limitations such as the presence of precipitation collection points, distance to weather information provision roads, and the presence of mountains. Therefore, this study intends to perform a comparative analysis by time zone and administrative dong provided by the Meteorological Administration using the wiper information among the information contained in the PVD(Probe Vehicle Data) collected from the highway C-ITS project. As a result of the analysis it was possible to detect rainfall even in the event of local rainfall and rainfall over a long period of time and the higher the cumulative precipitation per hour, the higher the probability of coincidence. This study is meaningful because it used PVD to solve the limitations of the existing road weather information provision method and suggested utilization plan for PVD.

• Journal of Korean Society of Transportation
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• v.29 no.5
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• pp.121-138
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• 2011

More affordable and available cutting-edge technologies (e.g., wireless vehicle communication) are regarded as a possible alternative to the fixed infrastructure-based traffic information system requiring the expensive infrastructure investments and mostly implemented in the uninterrupted freeway network with limited spatial system expansion. This paper develops an advanced decentralized traveler information System (ATIS) using vehicle-to-vehicle (V2V) communication system whose performance (drivers' travel time savings) are enhanced by three complementary functions (autonomous automatic incident detection algorithm, reliable sample size function, and driver behavior model) and evaluates it in the typical $6{\times}6$ urban grid network with non-recurrent traffic state (traffic incident) with the varying key parameters (traffic flow, communication radio range, and penetration ratio), employing the off-the-shelf microscopic simulation model (VISSIM) under the ideal vehicle communication environment. Simulation outputs indicate that as the three key parameters are increased more participating vehicles are involved for traffic data propagation in the less communication groups at the faster data dissemination speed. Also, participating vehicles saved their travel time by dynamically updating the up-to-date traffic states and searching for the new route. Focusing on the travel time difference of (instant) re-routing vehicles, lower traffic flow cases saved more time than higher traffic flow ones. This is because a relatively small number of vehicles in 300vph case re-route during the most system-efficient time period (the early time of the traffic incident) but more vehicles in 514vph case re-route during less system-efficient time period, even after the incident is resolved. Also, normally re-routings on the network-entering links saved more travel time than any other places inside the network except the case where the direct effect of traffic incident triggers vehicle re-routings during the effective incident time period and the location and direction of the incident link determines the spatial distribution of re-routing vehicles.

• Journal of Korean Society of Transportation
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• v.19 no.3
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• pp.115-131
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• 2001

The Purpose of this study is to develop a simulation model for large-scale network with interrupted flow as well as uninterrupted flow. The Cell Transmission(CT) theory is used to simulate traffic flow. Flow transition rules have been newly developed to simulate traffic flows at merging and diverging sections, and signalized intersections. In the model, it is assumed that dynamic OD table is exogenously given. Simulation results for toy network shows that the model can explain queue dynamics not only in signalized intersections of urban arterials, but also in merging and diverging sections of freeway. In case study, the model successfully simulated traffic flows of 145,000 vehicles on CBD network of city of Seoul with 74 traffic zones, 133 signalized intersections among 395 nodes and 1110 links.