• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.9
• /
• pp.3598-3614
• /
• 2020

With the increase of motor vehicles and tourism demand, some traffic problems gradually appear, such as traffic congestion, safety accidents and insufficient allocation of traffic resources. Facing these challenges, a model of Spatio-Temporal Dilated Convolutional Network (STDGCN) is proposed for assistance of extracting highly nonlinear and complex characteristics to accurately predict the future traffic flow. In particular, we model the traffic as undirected graphs, on which graph convolutions are built to extract spatial feature informations. Furthermore, a dilated convolution is deployed into graph convolution for capturing multi-scale contextual messages. The proposed STDGCN integrates the dilated convolution into the graph convolution, which realizes the extraction of the spatial and temporal characteristics of traffic flow data, as well as features of road occupancy. To observe the performance of the proposed model, we compare with it with four rivals. We also employ four indicators for evaluation. The experimental results show STDGCN's effectiveness. The prediction accuracy is improved by 17% in comparison with the traditional prediction methods on various real-world traffic datasets.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.4
• /
• pp.92-106
• /
• 2017

The adverse weather is known as a factor that interrupts traffic flow and causes traffic accidents and traffic congestion by lowering visibility of drivers. Especially, in case of fog unlike any other weather conditions, traffic accidents lead to serious accidents and the fatality of the accidents is known to be high. This paper aims to analyze uninterrupted traffic flow characteristics under foggy conditions among adverse weathers. The traffic volumes and speeds under foggy and normal conditions were analyzed. Results indicated that fog with low visibility causes the most insignificant reduction in traffic volumes. On the other hand, the reduction in the speeds due to low visibility was evident. In addition, the relationship between flow, speed, and density in fog were analyzed. Analysis results showed that the fog with less than 200m visibility had clear impact on traffic flow.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2010.09a
• /
• pp.1328-1332
• /
• 2010

The enlargement of existing tunnels is required to cope with problems related to traffic congestion. Sometimes, the tunnel traffic must be maintained through existing tunnels during their reconstruction due to non-availability of detours. And excavation by drill and blasting is desired for widening a hard rock tunnel. In this case, the road must be closed for some period for blasting through analyzing of traffic volume. In this paper, a case study on some traffic countermeasures for tunnel enlargement by blasting was performed. And the traffic flow characteristics of some tunnels in domestic main city were analyzed.

• Journal of Korean Port Research
• /
• v.13 no.2
• /
• pp.333-350
• /
• 1999

Today freeway is thought to be a very important transportation facility carrying tremendous traffic flow as the main corridor within the area of between the areas. However freeway is experiencing severe congestion and accidents by increased entrance ramp flow especially at peak time period. Ramp meters on the freeway entrance ramps that supply traffic to the freeway in a measured or appropriately regulated amount are needed for alleviating freeway congestion. Because ramp meters can be operated to discharge traffic at a measured or regulated rate thus maintaining more uniform speed on the mainline section maximizing the throughput to the freeway within the capacity of a downstream bottleneck and reducing the congestion related accidents. Thus the objectives in this study were to analyze the traffic characteristics on the freeway I-94 with ramp metering system before/after ITS technology in Detroit (Michigan) area compare shifts of the traffic characteristics on the freeway I-94 before/after ITS technology and finally suggest a better ramp metering strategy for the freeway system The following results were obtained: i)Flow occupancies and speeds on the mainline merge section of freeway were shown to be a big difference depending on the peak periods areas and directions based on the distribution of traffic flow characteristics on the freeway. ii)Reduced speed was shown to be more than 5 mph and ramp flow was also shown to be more than 240 vph at peak periods if there was the ramp metering system constructed on the freeway. iii)Ramp metering system was shown to be optimally operated on the freeway if ramp flow could be maximized within the range of over 900 vph and reduced occupancy could be also maximized by no more than 2 percent at peak periods. iv)The average flows on the freeway after the ITS technology were shown to be a decrease of over 20% depending on the peak periods areas and directions when compared with those flow on the freeway before the ITS technology. over 20% depending on the peak periods areas and directions when compared with those speeds on the freeway before the ITS technology. vi)The average metering rates on the freeway after the ITS technology were shown to be an increase of over 10% depending on the peak periods areas and directions when compared with those metering rates on the freeway before the ITS technology.

• Journal of Urban Science
• /
• v.7 no.1
• /
• pp.45-54
• /
• 2018

The purpose of this study is to find the factors that reduce prediction error in traffic volume using highway traffic volume data. The ARIMA model was used to predict the day, and it was confirmed that weekday and weekly characteristics were distinguished by prediction error. The forecasting results showed that weekday characteristics were prominent on Tuesdays, Wednesdays, and Thursdays, and forecast errors including MAPE and MAE on Sunday were about 15% points and about 10 points higher than weekday characteristics. Also, on Friday, the forecast error was high on weekdays, similar to Sunday's forecast error, unlike Tuesday, Wednesday, and Thursday, which had weekday characteristics. Therefore, when forecasting the time series belonging to Friday, it should be regarded as a weekly characteristic having characteristics similar to weekend rather than considering as weekday.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.2
• /
• pp.45-53
• /
• 2009

The fast progress on multimedia data acquisition technologies has enabled collecting vast amount of videos in real time. Although the amount of information gathered from these videos could be high in terms of quantity and quality, the use of the collected data is very limited typically by human-centric monitoring systems. In this paper, we propose a framework for analyzing long traffic video using series of content-based analyses tools. Our framework suggests a method to integrate theses analyses tools to extract highly informative features specific to a traffic video analysis. Our analytical framework provides (1) re-sampling tools for efficient and precise analysis, (2) foreground extraction methods for unbiased traffic flow analysis, (3) frame property analyses tools using variety of frame characteristics including brightness, entropy, Harris corners, and variance of traffic flow, and (4) a visualization tool that summarizes the entire video sequence and automatically highlight a collection of frames based on some metrics defined by semi-automated or fully automated techniques. Based on the proposed framework, we developed an automated traffic flow analysis system, and in our experiments, we show results from two example traffic videos taken from different monitoring angles.

• ETRI Journal
• /
• v.30 no.2
• /
• pp.183-193
• /
• 2008

In this paper, we propose quality of service mechanisms for flow-based routers which have to handle several million flows at wire speed in high-speed networks. Traffic management mechanisms are proposed for guaranteed traffic and non-guaranteed traffic separately, and then the effective harmonization of the two mechanisms is introduced for real networks in which both traffic types are mixed together. A simple non-work-conserving fair queuing algorithm is proposed for guaranteed traffic, and an adaptive flow-based random early drop algorithm is proposed for non-guaranteed traffic. Based on that basic architecture, we propose a dynamic traffic identification method to dynamically prioritize traffic according to the traffic characteristics of applications. In a high-speed router system, the dynamic traffic identification method could be a good alternative to deep packet inspection, which requires handling of the IP packet header and payload. Through numerical analysis, simulation, and a real system experiment, we demonstrate the performance of the proposed mechanisms.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.11 no.6
• /
• pp.31-39
• /
• 2012

This study aims to suggest a methodology of localizing and calibrating parameters, such as acceleration, deceleration, and lane changing which are the basis of car following model in interrupted traffic flow to overcome the limitation of origin and destination based transportation simulation and to verify the application of activity-based model for use in Korean roadway condition in a large scale area or a city. Especially, we figured out that a proper cell size reflecting Korean traffic conditions is 1.0m rather than 7.5m which is default size and a methodology of tracking vehicle behavior characteristics through tracking vehicle ID is suggested on this study. In addition, vehicle running characteristics in real interrupted traffic flow is analyzed through subdividing vehicle types and updating vehicle type ratio. For verification of suggested model, some portion of Dalgubyul-ro in the Daegu city is tested, and the possibility of realization of interrupted traffic flow in simulation is studied.

• Journal of the Ergonomics Society of Korea
• /
• v.26 no.2
• /
• pp.89-102
• /
• 2007

Generally, it is well known that driving in tunnel imposes large burden to driver because of spatial constraint, limited visual field and so on. And such a burden of driver result in high accident occurrence. In this reason, studies dealing with features of driving and traffic flow in tunnel have been performed. However, information about characteristics of drivers and traffic in a very long tunnel is not accumulated yet. The purpose of this study is to identify the relations between tunnel length and burden of driver, driving patterns, traffic flow characteristics using the tunnel simulator that realizing various tunnel situations. For this, the tunnel simulation program was developed along 11km-length section. And biological data of 10 subjects gained from driving condition in simulation program was analyzed and compared with the result of real driving condition.

• International Journal of Automotive Technology
• /
• v.7 no.2
• /
• pp.145-154
• /
• 2006

In the companion paper, the composition and structure of the MATDYMO (Multi-Agent for Traffic Simulation with Vehicle Dynamic Model) were proposed. MATDYMO consists of the road management system, the vehicle motion control system, the driver management system, and the integration control system. Among these systems, the road management system and the integration control system were discussed In the companion paper. In this paper, the vehicle motion control system and the driver management system are discussed. The driver management system constructs the driver agent capable of having different driving styles ranging from slow and careful driving to fast and aggressive driving through the yielding index and passing index. According to these indices, the agents pass or yield their lane for other vehicles; the driver management system constructs the vehicle agents capable of representing the physical vehicle itself. A vehicle agent shows its behavior according to its dynamic characteristics. The vehicle agent contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation is conducted for an interrupted flow model and its results are verified by comparison with the results from a commercial software, TRANSYT-7F. The interrupted flow model simulation is implemented for three cases. The first case analyzes the agents' behaviors in the interrupted flow model and it confirms that the agent's behavior could characterize the diversity of human behavior and vehicle well through every rule and communication frameworks. The second case analyzes the traffic signals changed at different intervals and as the acceleration rate changed. The third case analyzes the effects of the traffic signals and traffic volume. The results of these analyses showed that the change of the traffic state was closely related with the vehicle acceleration rate, traffic volume, and the traffic signal interval between intersections. These simulations confirmed that MATDYMO can represent the real traffic condition of the interrupted flow model. At the current stage of development, MATDYMO shows great promise and has significant implications on future traffic state forecasting research.