• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.14-26
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• 2009

This study presented a novel method to estimate travel times under incident conditions. Predictive travel time information was defined and evaluated with the proposed method. The proposed method utilized individual vehicle speeds obtained from global positioning systems (GPS) and inter-vehicle communications(IVC) for more reliable real-time travel times. Individual vehicle trajectory data were extracted from microscopic traffic simulations using AIMSUN. Market penetration rates (MPR) and IVC ranges were explored with the accuracy of travel times. Relationship among travel time accuracy, IVC ranges, and MPR were further identified using regression analyses. The outcomes of this study would be useful to derive functional requirements associated with traffic information systems under forthcoming ubiquitous transportation environment

• 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.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2788-2790
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• 2002

In this paper, we designed neural network predictive two degree of freedom PID controller to control sway of crane Crane's trolley arrive minimum oscillation of transfer body and establishment position in minimum time. When various establishment location and surrounding disturbance were approved based on mathematical modeling of crane, controller designed to become effective control location error and oscillation angle of two control variables that simultaneously can predictive control. We wish to develop automatic travel control system through anti-sway skill of crane.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.1-9
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• 2010

Predictive information on the freeway incident impacts can be a critical criterion in selecting travel options for users and in operating transportation system for operators. Provided properly, users can select time-effective route and operators can effectively run the system efficiently. In this study, a model is proposed to predict freeway incident impacts. The predictive model for incident impacts is based on short-term prediction. The proposed models are examined using MARE. The analysis results suggest that the models are accurate enough to be deployed in a real-world. The development of microscopic models to predict incident effects is expected to help minimize traffic delay and mitigate related social costs.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.1 s.4
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• pp.31-44
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• 2004

The study of Estimation model for the short-term travel time prediction. There is a different solution which has predicted the link travel time to solve this problem. By using this solution, the link travel time is predicted based on link conditions from time to time. The predicated link travel time is used to search the shortest path. Before providing a dynamic shortest path finding, the prediction model should be verified. To verify the prediction model, three models such as Kalman filtering, Stochastic Process, ARIMA. The ARIMA model should adjust optimal parameters according to the traffic conditions. It requires a frequent adjustment process of finding optimal parameters. As a result of these characteristics, It is difficult to use the ARIMA model as a prediction. Kalman Filtering model has a distinguished prediction capability. It is due to the modification of travel time predictive errors in the gaining matrix. As a result of these characteristics, the Kalman Filtering model is likely to have a non-accumulative errors in prediction. Stochastic Process model uses the historical patterns of travel time conditions on links. It if favorably comparable with the other models in the sense of the recurrent travel time condition prediction. As a result, for the travel time estimation, Kalman filtering model is the better estimation model for the short-term estimation, stochastic process is the better for the long-term estimation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.467-476
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• 2010

Travel delay (TD) denotes a time difference between the running time of vehicle with a normal speed and the travel time of vehicle with a reduced speed for traversing the same segment of roadway, and is sometimes used as a measure of time delayed in the junction or bottleneck areas of roadway. Urban freeways in the foreign countries are often suffering from traffic delay within the entrance and exit ramp junction influence areas, as a freeway with the speed limit of 80 km/h or higher only during the rush hours, but those in our country are especially experiencing severe traffic delay on the mainline segments as well as within the entrance and exit ramp junction influence areas, as a freeway with the speed limit of 80 km/h or less regardless of the rush hours. So, the purpose in this study is to develop the models that could predict the travel delay within the ramp junction influence areas of urban freeway having the geographical features which differ from the expressway, and also examine the validity of the travel delay predictive models developed.

• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.582-587
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• 2014

This study have researched on feasibility of bioelectrical impedance analysis (BIA, which is simple useful evaluation tool for predictive factor of cardiovascular disease) to patients who have to travel along the sea for a long-period time and have difficulty in visiting medical institutions. We studied on the basis of total cholesterol value, which is nowadays widely used tool for predictive factor of cardiovascular disease, and also studied its association with BIA value via statistical analysis. Our result showed correlation with fat thickness of individual sites, and especially, fat thickness of left thigh showed high relation with total cholesterol value. This result shows that people who are in travel of long-period of time at sea are feasible of using BIA to evaluate changes of left thigh fat thickness as predictive factor for cardiovascular disease. Due to lack of advanced researches further studies should be done. And based on special circumstances in sea, more studies should be done to validity concerning this circumstances and accuracy of this evaluation tool.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.5
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• pp.307-314
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• 2005

In this paper, we propose a predictive system for the avoidance of the moving obstacle. In the dynamic environment, robots should travel to the target point without collision with the moving obstacle. For this, we need the prediction of the position and velocity of the moving obstacle. So, we use the Kalman filer algorithm for the prediction. And for the application of the Kalman filter algorithm about the real time travel, we obtain the position of the obstacle which has the future time using Fuzzy system. Through the computer simulation studies, we show the effectiveness of the proposed navigational algorithm for autonomous mobile robots.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.833-839
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• 2019

Bus Information System (BIS) collects information related to the operation of buses and provides information to users through predictive algorithms. Method of predicting through recent information in same section reflects the traffic situation of the section, but cannot reflect the characteristics of the target line. The method of predicting the historical data at the same time zone is limited in forecasting peak time with high volatility of traffic flow. Therefore, we developed a pattern recognition bus arrival time prediction algorithm which could be overcome previous limitation. This method recognize the traffic pattern of target flow and select the most similar past traffic pattern. The results of this study were compared with the BIS arrival forecast information history of Seoul. RMSE of travel time between estimated and observed was approximately 35 seconds (40 seconds in BIS) at the off-peak time and 40 seconds (60 seconds in BIS) at the peak time. This means that there is data that can represent the current traffic situation in other time zones except for the same past time zone.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.35-41
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• 2006

In this paper, we develop anti-sway control in proposed techniques for an ATC system. The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate. Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2-DOF PID controller. The experimental results jar an ATC simulator show that the proposed control scheme guarantees performances, trolley position, sway angle, and settling time in NNP PID controller than other controller. As a result, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard.