• International Journal of Highway Engineering
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• v.18 no.5
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• pp.117-125
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• 2016

PURPOSES : The density in uninterrupted traffic flow facilities plays an important role in representing the current status of traffic flow. For example, the density is used for the primary measures of effectiveness in the capacity analysis for freeway facilities. Therefore, the estimation of density has been a long and tough task for traffic engineers for a long time. This study was initiated to evaluate the performance of density values that were estimated using VDS data and two traditional methods, including a method using traffic flow theory and another method using occupancy by comparing the density values estimated using vehicular trajectory data generated from a radar detector. METHODS : In this study, a radar detector which can generate very accurate vehicular trajectory within the range of 250 m on the Joongbu expressway near to Dongseoul tollgate, where two VDS were already installed. The first task was to estimate densities using different data and methods. Thus, the density values were estimated using two traditional methods and the VDS data on the Joongbu expressway. The density values were compared with those estimated using the vehicular trajectory data in order to evaluate the quality of density estimation. Then, the relationship between the space mean speed and density were drawn using two sets of densities and speeds based on the VDS data and one set of those using the radar detector data. CONCLUSIONS : As a result, the three sets of density showed minor differences when the density values were under 20 vehicles per km per lane. However, as the density values become greater than 20 vehicles per km per lane, the three methods showed a significant difference among on another. The density using the vehicular trajectory data showed the lowest values in general. Based on the in-depth study, it was found out that the space mean speed plays a critical role in the calculation of density. The speed estimated from the VDS data was higher than that from the radar detector. In order to validate the difference in the speed data, the traffic flow models using the relationships between the space mean speed and the density were carefully examined in this study. Conclusively, the traffic flow models generated using the radar data seems to be more realistic.

• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1496-1509
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• 2005

In this paper, an adaptive license plate recognition system which detects and recognizes license plate at real-time by using projected plane convolution and Decision Tree Classifier is proposed. And it was tested in circumstances which presence of complex background. Generally, in expressway tollgate or gateway of parking lots, it is very difficult to detect and segment license plate because of size, entry angle and noisy problem of vehicles due to CCD camera and road environment. In the proposed algorithm, we suggested to extract license plate candidate region after going through image acquisition process with inputted real-time image, and then to compensate license size as well as gradient of vehicle with change of vehicle entry position. The proposed algorithm can exactly detect license plate using accumulated edge, projected convolution and chain code labeling method. And it also segments letter of license plate using adaptive binary method. And then, it recognizes license plate letter by applying hybrid pattern vector method. Experimental results show that the proposed algorithm can recognize the front and rear direction license plate at real-time in the presence of complex background environments. Accordingly license plate detection rate displayed $98.8\%$ and $96.5\%$ successive rate respectively. And also, from the segmented letters, it shows $97.3\%$ and $96\%$ successive recognition rate respectively.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.51-61
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• 2002

In this dissertation, We demonstrated the Travel Time forecasting model in the freeway of multi-section with regard of drives' attitude. Recently, the forecasted travel time that is furnished based on expected travel time data and advanced experiment isn't being able to reflect the time-lag phenomenon specially in case of long distance trip, so drivers don't believe any more forecasted travel time. And that's why the effects of ATIS(Advanced Traveler Information System) are reduced. Therefore, in this dissertation to forecast the travel time of the freeway of multi-section reflecting the time-lag phenomenon & the delay of tollgate, we used traffic volume data & TCS data that are collected by Korea Highway Cooperation. Also keep the data of mixed unusual to applicate real system. The applied model for forecasting is consisted of feed-forward structure which has three input units & two output units and the back-propagation is utilized as studying method. Furthermore, the optimal alternative was chosen through the twelve alternative ideas which is composed of the unit number of hidden-layer & repeating number which affect studying speed & forecasting capability. In order to compare the forecasting capability of developed ANN model. the algorithm which are currently used as an information source for freeway travel time. During the comparison with reference model, MSE, MARE, MAE & T-test were executed, as the result, the model which utilized the artificial neural network performed more superior forecasting capability among the comparison index. Moreover, the calculated through the particularity of data structure which was used in this experiment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.5
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• pp.1-13
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• 2011

Recently, a number of OBU(On Board Unit) have being spreaded since ETCS(Electronic Toll Collection System)using DSRC(Dedicated Short Range Communication) was installed in the tollgate of the whole country. Many R&D and commercialization related to ITS service using DSRC and OBU mentioned above are ongoing such as traffic information collection and provision and a signal control, and public traffic information and management and so on. Especially, there are many researches conducted(conducting) on traffic information collection and provision using communication between OBU and RSE. However, Standards for both DSRC application and traffic collection and provision are not established clearly yet. So we would like to suggest a method of traffic information collection and provision without changing of standard related to DSRC. This method is to put the traffic messages into the existing Action primitive for ETC, which is described on "Technical criterion IV of basic traffic information exchange" which was notified by Ministry of Land, Transport and Maritime Affairs. Proposed standard application method is applied both to RSE and OBE. It is the same system which ETCS used in highway, currently. We confirmed the efficiency and performance of the system through conducting a variety of driving test using 4 vehicles in real road condition. Result of the real road test shows the effectiveness and validity of this method with about 97% communication success rate and based on studying the cases of 3% communication failure, we can analyse the expected problems in traffic information collection and provision using this method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.521-528
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• 2016

The tollbooths of a main motorway toll plaza are usually operated proactively responding to the variations of traffic demands of two-type vehicles, i.e. cars and the other (heavy) vehicles, respectively. In this vein, it is one of key elements to forecast accurate traffic volumes for the two vehicle types in advanced tollgate operation. Unfortunately, it is not easy for existing univariate short-term prediction techniques to simultaneously generate the two-vehicle-type traffic demands in literature. These practical and academic backgrounds make it one of attractive research topics in Intelligent Transportation System (ITS) forecasting area to forecast the future traffic volumes of the two-type vehicles at an acceptable level of accuracy. In order to address the shortcomings of univariate short-term prediction techniques, a Multiple In-and-Out (MIO) forecasting model to simultaneously generate the two-type traffic volumes is introduced in this article. The MIO model based on a non-parametric approach is devised under the on-line access conditions of large-scale historical data. In a feasible test with actual data, the proposed model outperformed Kalman filtering, one of a widely-used univariate models, in terms of prediction accuracy in spite of multivariate prediction scheme.

• Journal of Environmental Health Sciences
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• v.43 no.5
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• pp.370-381
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• 2017

Objectives: The rate at which the nationwide highway is outsourcing the duties of toll gate cashiers to the public is increasing. The aim of this study is to conduct research on job stress for the rate at which the fares are collected by national highway toll gate cashiers. Methods: The population selected was a statistically significant group making up 10% of the total number of people surveyed in 2015, with a population of approximately 5,495 persons. The sample size is intended to cover the maximum sample size of 550 samples and the maximum number of samples that should be obtained. After allocating the number of samples by quota allocation, the qualitative function of Quality Function Deployment (QFD) was applied by random sampling. Results: Job stress ranked at $46.6{\pm}11.5$ points was found to be under the stress of 50% reported in other occupations. Job stress items showed higher for "job instability" compared to other types of tasks. Also, it appeared lower in "conflict in relationships." This is a result of the work characteristics of highway service operators. Conclusions: Time was found to have the highest influence on the workload (${\beta}=0.80$, p. 0.001), which calls for a reduction in time and workload. est influence on the workload (${\beta}=0.80$, p. 0.001), which requires a reduction in time and workload.