• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.21-32
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• 2007

The households to be surveyed are usually huge number at the level of a city or metropolitan survey, not to mention a nationwide travel survey. Therefore, household travel surveys to figure out true origin-destination (O/D) trip patterns (population O/D) are conducted through a sampling method rather than by surveying all of the population in the system. Therefore, the population O/D pattern can only be estimated by expanding the sampled O/D patterns to the population. It is very difficult to avoid the errors involved in the process of sampling, surveying and expanding O/D data. In order to minimize such errors while estimating the true O/D patterns of the population, the validation and adjustment process should employed by doing a comparison between the expanded sample O/D data and observed link traffic volumes. This study suggests a method of validation and adjustment of the expanded sample O/D data by comparing observed link volumes at several screenlines. The study also suggests a practical technique to modify O/D pairs which are excluded in the screenline validation process by comparing observed traffic volume with the results of traffic assignment analysis. An empirical study was also conducted as an example applying the suggested methods of validation and adjustment with Korea's nationwide O/D data and highway network.

• Journal of Navigation and Port Research
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• v.43 no.6
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• pp.413-419
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• 2019

Traffic routes typically have heavy traffic. Especially, the entrance of the route has a high risk of accidents occurring because of ships entering and exiting the port. However, almost of studies have focused on the distribution of traffic on the route. Thus, studies on the distribution between ships for passing through the route are insufficient. The purpose of this study was to analysis the traffic in the Busan north port No.1 route for one week. Based on present traffic conditions, one gate line was settled on the route with an analysis of traffic conditions. Based on the analysis data, each optimal time probability distribution between ships was divided into inbound/outbound and traffic volume. An analysis of the optimal probability distribution, was applied to 31 probability distributions divided into bounded, unbounded, non-negative, and advanced probability distribution. The KS test was applied for identifying three major optimal time probability distributions. According to the KS test results, the Wakeby distribution is the best optimal time probability distribution on the designated route. Although the optimal time probability distribution for other transportation studies such as on vehicles on highways is a non-negative probability distribution, this distribution is an advanced probability distribution. Thus, the application of major probability distribution for using other transportation studies is not applicable to this study Additionally, the distance between ships in actual traffic surveys and the distance estimated by the optimal probability distribution were compared. As a result of the comparison, those distances were fairly similar. However, this study was conducted in only one major port. Thus, it is necessary to investigate the time between ships and calculate a traffic volume on varying routes in future studies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.119-131
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• 2024

Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.

• Journal of Navigation and Port Research
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• v.45 no.6
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• pp.306-313
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• 2021

National fishing harbour is as a refuge for fishing boats and a breakwater lighthouse is installed as a functional facility in consideration of harbour identification and the safety of passing vessels. In this study, the service level of breakwater lighthouse (234 units) was estimated based on the traffic volume of 105 national fishing harbour. For this purpose, the evaluation items were determined, the fishing harbour standard index was calculated (Fs=1), the proximity of fishing harbour was identified and the function (service level) of the breakwater lighthouse was estimated in the following order. However, national fishing harbour differed in size, traffic volume and fishing vessel capacity. Therefore, 105 national fishing harbour were divided into three groups through cluster analysis. The cluster analysis was based on the service level factors of the breakwater lighthouse, such as the number of weeding fishing vessels, tonnage of fishing vessels, the number of incoming and outgoing vessels per year, and fishing vessel capacity. As a result of the estimation, the service level of the breakwater lighthouse (light tower height, visual height, visual range, interval) was 10.50m, 16.50m, 7.00mile, 5.5sec for group 1, and 10.67m, 16.16m, 8.33mile, and 6.0sec for group 2, The three groups are 11.53m, 16.75m, 6.75mile and 5.0sec. The results of this study can be used as useful basic data for improving the service level of traffic vessels when a breakwater lighthouse is built in a fishing harbour in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.1
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• pp.73-80
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• 2018

In motorway traffic flow control, the conventional way based on real-time response has been changed into advanced way based on proactive response. Future traffic conditions over multiple time intervals are crucial input data for advanced motorway traffic flow control. It is necessary to overcome the uncertainty of the future state in order for forecasting multiple-period traffic volumes, as the number of uncertainty concurrently increase when the forecasting horizon expands. In this vein, multi-interval forecasting of traffic volumes requires a viable approach to conquer future uncertainties successfully. In this paper, a forecasting model is proposed which effectively addresses the uncertainties of future state based on the behaviors of temporal evolution of traffic volume states that intrinsically exits in the big past data. The model selects the past states from the big past data based on the state evolution of current traffic volumes, and then the selected past states are employed for estimating future states. The model was also designed to be suitable for data management systems in practice. Test results demonstrated that the model can effectively overcome the uncertainties over multiple time periods and can generate very reliable predictions in term of prediction accuracy. Hence, it is indicated that the model can be mounted and utilized on advanced data management systems.

• The Transactions of the Korea Information Processing Society
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• v.3 no.2
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• pp.369-380
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• 1996

Inductive Loop Detector(ILD) has been commonly used in collecting traffic data such as occupancy time and non-occupancy time. From the data, the traffic volume and type of passing vehicle is calculated. To provide reliable data for traffic control and plan, accuracy is required in type recognition which can be utilized to determine split of traffic signal and to provide forecasting data of queue-length for over-saturation control. In this research, a new recognition model issuggested for recognizing typeof vehicle from thecollected data obtained through ILD systems. Two clustering methods, based on statistical algorithms, and one neural network clustering method were employed to test the reliability and occuracy for the methods. In a series of experiments, it was found that the new model can greatly enhance the reliability and accuracy of type recongition rate, much higher than conventional approa-ches. The model modifies the neural network clustering method and enhances the recongition accuracy by iteratively applying the algorithm until no more unclustered data remains.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.1
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• pp.1-8
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• 2017

In this study, a congestion assessment was conducted to verify seasonal differences in congestion for major coastal traffic routes and fairways in major ports with GICOMS Data for 7 days without issuing a special weather report. As a result, a maximum of 11 % and 82 % are shown, with an average of 3.5 % and a 30 % seasonal difference for hourly average congestion and peak time congestion. Therefore, seasonal differences for the target area should be taken into consideration to perform further congestion assessments, particularly for maritime traffic safety assessments, and keen attention should be given to setting up safety measures against congestion.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.91-98
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• 2009

This paper presents a solution to error avalanche of deciphering where radio noise brings random bit errors in encrypted image data under ubiquitous environment. The image capturing module is to be made comprising data compression and encryption features to reduce data traffic volume and to protect privacy. Block cipher algorithms may experience error avalanche: multiple pixel defects due to single bit error in an encrypted message. The new fault tolerant scheme addresses error avalanche effect exploiting a three-dimensional data shuffling process, which disperses error bits on many frames resulting in sparsely isolated errors. Averaging or majority voting with neighboring pixels can tolerate prominent pixel defects without increase in data volume due to error correction. This scheme has 33% lower data traffic load with respect to the conventional Hamming code based approach.

• Journal of Korean Society of Transportation
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• v.13 no.4
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• pp.5-29
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• 1995

Advanced Traveler Inoformation Systems*ATIS) , as a subsystem of ITS influence the travel choices of dreivers by providing them with historical, real-time and predictive information to supprot travel decisions and consequently improves the speed and quality of travel. For thesuccessul accomplishment of ATIS, the time-dependent variations of traffic in a road network and travel times of vehicles during their journey must be predicted . The purpose of this study is to evaluate the past developments in the dynamic route choice models and to apply the instantaneous dynamic user optimal route choice model. recently formulated with flow propagation constraints by Ran, Boyce and LeBlanc, to the real transportation network of Seocho-Ku in Seoul. As input data for this application, the time-dependent travel rates are estimated and the link travel time function is derived. The modelis validated from three view points : the efficiency of model itself the ability to predict traffic volume and travel time on links, and the optimal traffic control.

• Journal of Korean Society of Transportation
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• v.34 no.1
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• pp.1-14
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• 2016

In the recent years, the internet has become accessible without limitation of time and location to anyone with smartphones. It resulted in more convenient travel information access both on the pre-trip and en-route phase. The main objective of this study is to conduct a stationary test for traffic information web/mobile application access indexes from TCS (Toll Collection System); and analyzing the relationship between the web/mobile application access indexes and actual traffic volume on expressways, in order to analyze searching behavior of expressway related travel information. The key findings of this study are as follows: first, the results of ADF-test and PP-test confirm that the web/mobile application access indexes by time periods satisfy stationary conditions even without log or differential transformation. Second, the Pearson correlation test showed that there is a strong and positive correlation between the web/mobile application access indexes and expressway entry and exit traffic volume. In contrast, truck entry traffic volume from TCS has no significant correlation with the web/mobile application access indexes. Third, the time gap relationship between time-series variables (i.e., concurrent, leading and lagging) was analyzed by cross-correlation tests. The results indicated that the mobile application access leads web access, and the number of mobile application execution is concurrent with all web access indexes. Lastly, there was no web/mobile application access indexes leading expressway entry traffic volumes on expressways, and the highest correlation was observed between webpage view/visitor/new visitor/repeat visitor/application execution counts and expressway entry volume with a lag of one hour. It is expected that specific individual travel behavior can be predicted such as route conversion time and ratio if the data are subdivided by time periods and areas and utilizing traffic information users' location.