• Journal of Korean Society of Transportation
• /
• v.34 no.5
• /
• pp.476-488
• /
• 2016

This study reviewed factors and causes that affect on reliability and accuracy of transportation demand forecasting. In general, the causes of forecasting errors come from variety and irregularity of trip behaviors, data limitation, data aggregation and model simplification. Theoretical understanding about the inevitable errors will be helpful for reasonable decision making for practical transportation policies. The study especially focused on traffic assignment with the KTDB data, and described the factors and causes of errors by classifying six categories such as (1) errors in input data, (2) errors due to spacial aggregation and representation method of network, (3) errors from representing values for variations of traffic patterns, (4) errors from simplification of traffic flow model, and (5) errors from aggregation of route choice behavior.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.6
• /
• pp.336-342
• /
• 2017

Traffic can be localized by reducing the traffic load on the physical network by causing traffic to be generated at the end of the packet network. By localizing traffic, the IoT-based sensitive data-related security issues can be supported effectively. In addition, it can be applied effectively to the next-generation smart network environment without changing the existing network infrastructure. In this paper, a content priority scheme was applied to smart network-based IoT data. The IoT contents were localized to efficiently pinpoint the flow of traffic on the network to enable smart forwarding. In addition, research was conducted to determine the effective network traffic routes through content localization. Through this study, the network load was reduced. In addition, it is a network structure that can guarantee user quality. In addition, it proved that the IoT service can be accommodated effectively in a smart network-based environment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.4
• /
• pp.287-296
• /
• 2015

Recent navigation systems provide quick guide services, based on processing real-time traffic information and past traffic information by applying predictable pattern for traffic information. However, the current pattern for traffic information predicts traffic information by processing past information that it presents an inaccuracy problem in particular circumstances(accidents and weather). So, this study presented a more precise predictive traffic information system than historical traffic data first by analyzing route search data which the drivers ask in real time for the quickest way then by grasping traffic congestion levels of the route in which future drivers are supposed to locate. First results of this study, the congested route from Yang Jae to Mapo, the analysis result shows that the accuracy of the weighted value of speed of existing commonly congested road registered an error rate of 3km/h to 18km/h, however, after applying the real predictive traffic information of this study the error rate registered only 1km/h to 5km/h. Second, in terms of quality of route as compared to the existing route which allowed for an earlier arrival to the destination up to a maximum of 9 minutes and an average of up to 3 minutes that the reliability of predictable results has been secured. Third, new method allows for the prediction of congested levels and deduces results of route searches that avoid possibly congested routes and to reflect accurate real-time data in comparison with existing route searches. Therefore, this study enabled not only the predictable gathering of information regarding traffic density through route searches, but it also made real-time quick route searches based on this mechanism that convinced that this new method will contribute to diffusing future traffic flow.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.6D
• /
• pp.779-784
• /
• 2011

Freeway FFS (Free-Flow Speed) under the state of LOS (Level of Service) A has been regarded as a homogeneous state to all levels of traffic volume. The features of low-density FFS is served as the basic data for a decision on limited maximal speed, accident analysis, simulation modeling etc. A few researches for the macroscopic characteristics of design and operation speed have been reported, and any study for the microscopic features of freeway free-flow speed under the state of low density has not been done. Therefore, the characteristics of low-density FFS according to the level of traffic volume (1-3 veh/30 sec) and daily hour periods (0-5, 6-8, 9-11, 12-19, 20-23) is microscopically analyzed in this study with huge volume and speed data. It was found that speed distributions are changed and show different behaviors under the conditions of traffic volume levels and daily time periods. V85s (85th percentile speed) at early morning and night periods decrease when levels of traffic volume increase, whereas V85s at day time do not show considerable differences. Especially, FFSs of levels of traffic volume at early morning and night periods, despite low density, is analyzed as heterogeneity, but homogeneity at day time.

• Journal of Korean Society of Transportation
• /
• v.34 no.2
• /
• pp.146-157
• /
• 2016

The objective of this study is to actualize a statistical model of the 3-detector simplification model, which was proposed to detect outbreak situations by Daganzo in 1997 and to verify the statistical appropriacy thereof. This study presents the calculation process of the 3-detector simplification model and realizes the process using a statistics program. Firstly, the model was applied using data on detector of the main highways on which there is no entrances or exits. Moreover, in order to statistically verify the 3-detector simplification model, accumulative traffics for 30 seconds period, which reflects the dynamic changes of traffics due to shock wave, were estimated for outbreak traffics and steady flow, and the error of acquired data was statistically compared with that of the actual accumulative traffics. As a result, the error ratio between steady and incident cumulative flows has reached its maximum after 2-3 hours from an accident. Moreover, the incident traffic flows by accidents and the stade flows are heterogeneous in terms of their dispersion and means.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.3
• /
• pp.255-263
• /
• 2014

Today, a number of CCTV on the highway is to observe the flow of traffics. There have been a number of studies where traffic data (e.g., the speed of vehicles and the amount of traffic on the road) are transferred back to the centralized server so that an appropriate action can be taken. This paper introduces a system that detects the changes of traffic flows caused by an accident or unexpected stopping (i.e., vehicle remains idle) by monitoring each lane separately. The traffic flows of each lane are level spacing curve that shows Wigner distribution for location vector. Applying calogero-moser system and Hamiltonian system, probability equation for each level-spacing curve is derived. The high level of modification of the signal means that the lane is in accident situation. This is different from previous studies in that it does more than looking for the signal from only one lane, now it is able to detect an accident in entire flow of traffic. In process of monitoring traffic flow of each lane, when camera recognizes a shadow of vehicle as a vehicle, it will affect the accident detecting capability. To prevent this from happening, the study introduces how to get rid of such shadow. The system using Basian network method is being compared for capability evaluation of the system of the study. As a result, the system of the study appeared to be better in performance in detecting the modification of traffic flow caused by idle vehicle.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.30 no.4
• /
• pp.1-8
• /
• 2022

In this study, we propose trajectory-based arrival management using CDO (Continuos Descent Operations). The operational procedures with TBO (Trajectory-Based Operations) concept were established to allow aircraft and ground system to share the trajectories with each other in real time. The proposed operational concept was validated in the air traffic control simulation environment, which consists of controller working position, pseudo pilot system, air traffic generation system, and controllers' decision support system for arrival management using CDO. Simulation results compared with actual flight data indicate that proposed concept could improve the efficiency of traffic flow management in terms of total descending time and fuel consumption. And it was confirmed that if there is a system that can share and utilize the synchronized trajectory, it can be helpful to control arrival aircraft and apply CDO concept.

• Journal of Korean Society of Transportation
• /
• v.35 no.3
• /
• pp.220-233
• /
• 2017

Traffic volumes are fundamental data widely used in various traffic analysis, such as origin-and-destination establishment, total traveled kilometer distance calculation, congestion evaluation, and so on. The low number of links collecting the traffic-volume data in a large urban highway network has weakened the quality of the analyses in practice. This study proposes a method to estimate the traffic volume data on a highway link where no collection device is available by introducing a spatial statistic technique with (1) the traffic-volume data from TOPIS, and National Transport Information Center in the Ministry of Land, Infrastructure, and (2) the navigation data from private navigation. Two different component models were prepared for the interrupted and the uninterrupted flows respectively, due to their different traffic-flow characteristics: the piecewise constant function and the regression kriging. The comparison of the traffic volumes estimated by the proposed method against the ones counted in the field showed that the level of error includes 6.26% in MAPE and 5,410 in RMSE, and thus the prediction error is 20.3% in MAPE.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.25 no.3
• /
• pp.298-305
• /
• 2019

The demand for the revitalization of marine tourism in Busan North Port is increasing due to changes in functions such as an increase in harbor traffic volume and the expansion of marine leisure space in Busan. As a result, Busan City plans to set a phased alleviation target for prohibition of cruise ship operations, and to lift the prohibition of excursion ship operations in North Port following the cancellation of the prohibition of excursion ship operations in South Port in 2017. The purpose of this study is to evaluate the risk of excursion ship operations in Busan North Port by applying the marine traffic assessment index and to examine the possibility of excursion ship operations. For this purpose, port status, marine accidents, and traffic flow of Busan North Port were investigated. In addition, marine traffic assessment indexes, such as traffic congestion, risk based on an ES Model, and IWRAP MkII, a maritime risk assessment tool, were used to assess the risk and possibility of excursion ship operations in Busan North Port. This study can be used as basic data for analyzing the risk factors that may occur when excursion ships are operated in Busan North Port and to define how excursion ships should operate, with related safety measures.

• Journal of Korean Port Research
• /
• v.14 no.1
• /
• pp.66-75
• /
• 2000

From the traffic analysis, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results were obtained : ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy. ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period showed 10mph decrease when compared with the 24hours'average speed, but the speed did not show a big difference in the afternoon peak period. ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge section. ⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.