• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2297-2302
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• 2010

The status and effectiveness of Bi-modal Tram is analyzed through the comparison of the transport effectiveness and operation cost between the public transportation systems (bus, light rail transit) considering the vehicle and operation characteristic of new transit system Bi-modal Tram. The standard operation schedule is established in consideration of the vehicle specification and operation characteristic of main public transportation modes, and then the annual average operation cost is estimated depending on the volume, speed, analysis length for respective public transportation mode. Through analyzing the operation cost and distribution characteristic of public transportation modes depending on the transport volume and travel speed, the operational efficiency suitable for the city is derived. It is concluded that the operational efficiency of Bi-modal Tram is superior to that of the bus and light rail transit on the aspect of travel volume and operation speed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.142-155
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• 2019

This study was conducted with the aim of developing a system to collect taxi GPS probe information to prevent link defects and to improve the accuracy of the standard link-based travel speed by determining when to go into and come out the link. For this purpose, a framework and algorithm consisting of a five-step process for standard link-based map matching and individual vehicle travel speed are presented and used it to calculate the average travel speed of the service link. Two on-site surveys of Teheran and Hakdong-ro were conducted to verify the results by the methods proposed in this paper. On the basis of the overall time of the field survey, the deviation in the travel speed was 0.2 km/h and 0.6 km/h, the accuracy was 99% and 96%, and the MAPE(Mean Absolute Percentage Error) was 1% and 4% in Teheran and Hakdong-ro, respectively. These results were more accurate thand those obtained using conventional methodologies without standard links.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.5
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• pp.837-844
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• 2017

Generally, V/C ratio in uninterrupted traffic flow and average travel speed in interrupted traffic flow are utilized as measure of effect for assessing operational situation of roads. The set of road conditions and traffic conditions are considered to be major variables for assessing operational situation in the traffic flow. However, weather conditions such as rainfall also affect the operational situation of roads. The studies reflected by the rainy situation are conducted in the uninterrupted flow, but the related studies are insufficient in the interrupted flow. In this study, the modification factors during rainfall in the interrupted flow were suggested, and the factors could be used when calculating the average travel speed during rainfall in the interrupted flow. By utilizing the data that were investigated in the same road and traffic conditions and the different weather conditions (rainy day or clear day), the modification factors were founded on regression analysis of the travel speed during rainfall as a dependent variable. Modification factors was suggested in dividing peak time, non-peak time, and whole period. Based on this study, the modification factors can be used to complementing the average travel speed model for assessing the operational situation of urban streets during rainfall.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.40-48
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• 2012

In this paper, we suggests methods for determining optimal representative value and the optimal size of historical data for reliable travel speed prediction. To evaluate the performance of the proposed method in real world environments, we did field tests at four roadway links in Seoul on Tuesday and Sunday. According to the results of applying the methods to historical data of Central Traffic Information Center, the optimal representative value were analyzed to be average and weighted average. Second, it was analyzed that 2 months data is the optimal size of historical data used for travel speed prediction.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.85-92
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• 2012

PURPOSES : Since expressways in South Korea are toll roads, many trumpet type interchanges exist, resulting in the installation of loop ramps very frequently. While the travel speed of the main lane is designed to be 100-110 km/h, the structure of a loop ramp is different and is designed for a minimum speed of 40 km/h. In fact, most of the actual travel speeds measured on the ramp exceed the designated speed, which has been a major problem in traffic safety. In this research, a type of pavement marking speed-reduction treatment called the "Peripheral Transverse Line" is installed on expressway loop ramps in order to study the change of driving speeds after the installation. METHODS : To verify statistically the change, this speed-reduction treatment has been installed on the Chungju interchange and the Yeoju junction. The driving speeds before the installation were compared with driving speeds both one month and five monthsafter the installation. RESULTS : As a result, the reductions of the average driving speeds after the treatment were statistically significant. More specifically, the average driving speeds of the Chungju interchange were reduced by 7.1-7.7 % for its tangent road section, and the speeds decreased by 8.5-9.5 % for its curve section. Similarly, in the Yeoju junction, an average speed reduction of 2.9-4.8 % for its tangent section was measured, along with 3.9% long-term speed reduction for its curve section. CONCLUSIONS : Since the pavement marking speed-reduction treatment has been partially proven to be effective from this research, we expect to expand this treatment and re-confirm the effect from a long-term perspective in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.103-114
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• 2023

This study collected various data of urban roadways to analyze the effect of travel speed change, and a GRU-based short-term travel speed prediction model was developed using such big data. The baseline model and the double exponential smoothing model were selected as comparison models, and prediction errors were evaluated using the RMSE index. The model evaluation results revealed that the average RMSE of the baseline model and the double exponential smoothing model were 7.46 and 5.94, respectively. The average RMSE predicted by the GRU model was 5.08. Although there are deviations for each of the 15 links, most cases showed minimal errors in the GRU model, and the additional scatter plot analysis presented the same result. These results indicate that the prediction error can be reduced, and the model application speed can be improved when applying the GRU-based model in the process of generating travel speed information on urban roadways.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.124-132
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• 2012

There is high probability of children's traffic accidents. Because their physical, mental attribute are weak. Major part of the accidents happen during walking. Above all, jaywalking is the biggest traffic accident reason. Many traffic accidents take place on the road to school or near the home area. So Ministry of Public Administration and Security legislated children safeguard zone since 1995. But a study are inadequate the safety facilities on the effectiveness verification in the school zone. Therefore, this study aims to analyze the effectiveness of safety facilities. The vehicle speed is a direct correlation traffic accident. So in this study, the MOE(Measure of Effectiveness) is average travel speed in the school zone. The results shows that hump, rised pedestrian crossing has an effect.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.214-215
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• 2013

The main criteria for objective measure of the level of transportation service is travel time and delay time. In this paper, the level of service is measured by using moving vehicles method. Through this, we get the hourly traffic volume, the average travel time, space average speed, etc. In addition, we get the density of traffic.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.13-25
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• 2008

This study analyzed errors of data received from GPS which showed different reception characteristics based on chipset at poor reception area. The digital map made from National Police Agency shows 4% errors of length on the average. The comparison of three different algorithms - Average Spot Speed, Cumulative Travel Length from GPS with Actual Travel Time, Travel Length from Digital Map with Actual Travel Time have been conducted to find significant difference estimating travel time from GPS Data. The algorithm to estimate travel time from travel length and travel time showed the most reliable results from the others.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.47-59
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• 2000

The purpose of this study is to develop travel-time estimation model using neural networks and prediction model using neural networks and kalman-filtering technique. The data used in this study are travel speed collected from inductive loop vehicle detection systems(VDS) and travel time collected from the toll collection system (TCS) between Seoul and Osan toll Plaza on the Seoul-Pusan Expressway. Two models, one for travel-time estimation and the other for travel-time Prediction were developed. Application cases of each model were divided into two cases, so-called, a single-region and a multiple-region. because of the different characteristics of travel behavior shown on each region. For the evaluation of the travel time estimation and Prediction models, two Parameters. i.e. mode and mean were compared using five-minute interval data sets. The test results show that mode was superior to mean in representing the relationship between speed and travel time. It is, however shown that mean value gives better results in case of insufficient data. It should be noted that the estimation and the Prediction of travel times based on the VDS data have been improved by using neural networks, because the waiting time at exit toll gates can be included for the estimation of travel time based on the VDS data by considering differences between VDS and TCS travel time Patterns in the models. In conclusion, the results show that the developed models decrease estimation and prediction errors. As a result of comparing the developed model with the existing model using the observed data, the equality coefficients of the developed model was average 88% and the existing model was average 68%. Thus, the developed model was improved minimum 17% and maximum 23% rather then existing model .