• 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.5
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• pp.57-67
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• 2000

Two fuzzy travel time estimators for interrupted traffic flow were developed based on field survey data and simulation data 7hat is collected from DETSIM, which is microscopic traffic simulation model that car-following theory is applied. One is FETTOS(Fuzzy Estimator of Travel Time using Occupancy and Spot speed) and the other is FETTOS(Fuzzy Estimator of Travel Speed using Volume and Occupancy). Fuzzy logic controller was applied to the estimators to deal with non-linear relationship between traffic variables and travel time. According to results of simulation and field survey. estimation of travel time can be modeled by using percent occupancy better than any other traffic variables. Detector location from storyline and signal timing Plan of intersection are affected to estimate travel time. With a few findings, the estimator was constructed and its performance was tested for observed travel time data and simulated data. FETTOS which needs signal timing plan and detector location estimates travel time with accurate better than FETSVO does. However. FETSVO has excellent transferability because the estimator needs set of input data only; volume and time mean speed.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.55-76
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• 2000

We propose a general solution methodology for identifying the optimal aggregation interval sizes as a function of the traffic dynamics and frequency of observations for four cases : i) link travel time estimation, ii) corridor/route travel time estimation, iii) link travel time forecasting. and iv) corridor/route travel time forecasting. We first develop statistical models which define Mean Square Error (MSE) for four different cases and interpret the models from a traffic flow perspective. The emphasis is on i) the tradeoff between the Precision and bias, 2) the difference between estimation and forecasting, and 3) the implication of the correlation between links on the corridor/route travel time estimation and forecasting, We then demonstrate the Proposed models to the real-world travel time data from Houston, Texas which were collected as Part of the Automatic Vehicle Identification (AVI) system of the Houston Transtar system. The best aggregation interval sizes for the link travel time estimation and forecasting were different and the function of the traffic dynamics. For the best aggregation interval sizes for the corridor/route travel time estimation and forecasting, the covariance between links had an important effect.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.7-18
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• 2006

Data for travel information Provision are regularly aggregated to Provide travel time information in a reliable and convenient manner and to manage traffic data and information efficiently. In most of practices in Korea, the GPS based travel time data are mainly aggregated every 5 minutes As a result, some probes can't pass by a link within aggregation interval and thereby create uncompleted link passing data. But these data are mostly generated during the congested times and therefore a method that uses such uncompleted link passing data are required. This study estimated queue dissipation length, green time and cycle that use GPS spot speed and developed a link travel time estimation method using such uncompleted link passing data. It also presents method and the overall process of using such data to estimate link travel time in a more accurate manner. As a result, MAPE 1.98% and MAE 4.75 sec of link travel time accuracy improvement has been reported, which is not much different from the real link travel time. The method Proposed here would be an alternative to increase the amount of GPS probe data, especially in congested urban arterial case.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.537-545
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• 2018

Determination of the time parameters such as the travel time in the design flood is very important. The travel time is mainly used for flood and river management, and the travel time of non flood season is used for maintenance flow and management of the river. Estimation of travel time for natural rivers is mainly based on the geomorphological factors of the basin. In addition to the topographical factors, the travel time is calculated by considering the factors of the runoff curve, velocity and rainfall intensity. However, there is no study on the estimation of travel time considering both the rainfall condition and the soil moisture accounting by the frequency period. Therefore, the travel time calculation is divided into the case of setting the Hwanggang Dam and the Imjin bridge water level station of Imjin river as the natural river considering rainfall condition by the frequency period and the soil moisture accounting, and the case of traveling the Imjin bridge water level station according to the condition of outflow of the Hwanggang Dam. For the sections set as natural rivers, the results were verified by comparing with the newly developed travel time calculation method. Based on the results, the travel times of the Hwanggang Dam outflow conditions were calculated. The time to travel in this study can be secured flood control of the Imjin river basin and time to prepare for danger when outflowing the the Hwanggang Dam.

• Journal of Intelligence and Information Systems
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• v.4 no.2
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• pp.23-34
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• 1998

Travel time forecasting, especially public bus travel time forecasting in urban areas, is a difficult and complex problem which requires a prohibitively large computation time and years of experience. As the network of target area grows with addition of streets and lanes, computational burden of the forecasting systems exponentially increases. Even though the travel time between two neighboring intersections is known a priori, it is still difficult, if not impossible, to compute the travel time between every two intersections. For the reason, previous approaches frequently have oversimplified the transportation network to show feasibilities of the problem solving algorithms. In this paper, forecasting of the travel time between every two intersections is attempted based on travel time data between two neighboring intersections. The time stamps data of public buses which recorded arrival time at predetermined bus stops was extensively collected and forecast. At first, the time stamp data was categorized to eliminate white noise, uncontrollable in forecasting, based on wavelet conversion. Then, the radial basis neural networks was applied to remaining data, which showed relatively accurate results. The success of the attempt was confirmed by the drastically reduced relative error when the nodes between the target intersections increases. In general, as the number of the nodes between target intersections increases, the relative error shows the tendency of sharp increase. The experimental results of the novel approaches, based on wavelet conversion and neural network teaming mechanism, showed the forecasting methodology is very promising.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.233-239
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• 2006

Most research for until at now link travel time were research for mean link travel time calculate or estimate which uses the average of the individual vehicle. however, the link travel time distribution is divided caused by with the impact factor which is various traffic condition, signal operation condition and the road conditional etc. preceding study result for link travel time distribution characteristic showed that the patterns of going through traffic were divided up to 2 in the link travel times. therefore, it will be more accurate to divide up the link travel time into the one involving delay and the other without delay, rather than using the average link travel time in terms of assessing the traffic situation. this study is it analyzed transit hour distribution characteristic and a cause using examine to the variables which give an effect at link travel time distribute using simulation program and determinate link travel time distribute ratio estimation model. to assess the distribution of the link travel times, this research develops the regression model and the fuzzy model. the variables that have high level of correlations in both estimation models are the rest time of green ball and the delay vehicles. these variables were used to construct the methods in the estimation models. The comparison of the two estimation models-fuzzy and regression model- showed that fuzzy model out-competed the regression model in terms of reliability and applicability.

• Journal of Korean Society of Transportation
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• v.17 no.5
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• pp.69-78
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• 1999

This paper defines the reliable based route choice Principle and formulates the reliability based equilibrium traffic assignment using the Principle. The reliability is defined as the difference of travel demand and capacity using the interference theory of the system engineering. An efficient solution a1gorithm based on Frank-Wo1fe algolithm is Presented to calculate and compare the reliability based traffic assignment with conventional travel time based assignment using small and large scaled road networks. The results show that reliability based traffic assignment converges to equilibrium solution in a reasonable computing time. The equilibrium link flows between reliability and travel time based traffic assignment differ each other in the sense that reliability based assignment is assigned based on the maximum difference of travel demand and link capacity whilst travel time based is assigned on the shortest travel time.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.315-321
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• 2015

ATMS calculates section travel time using two-way communication system called DSRC(Dedicated Short Range Communications) which collects data of RSE (Road Side Equipment) and Hi-pass OBU (On-board Unit). Travel time estimation in urban area involves uncertainty due to the interrupted flow. This study not only analyzed real-time data but also considered pattern data. Baek-Je-Ro street in Jeon-Ju city was selected as a test site. Existing algorithm was utilized for data filtering and pattern data building. Analysis results repoted that travel time estimation with 20% of real-time data and 80% of pattern data mixture gave minimum average difference of 37.5 seconds compare to the real travel time at the 5% significant level. Results of this study recommend usage of intermixture between real time data and pattern data to minimize error for travel time estimation in urban area.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.1
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• pp.119-130
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• 1989

This paper presents average travel time models automated warehousing system where the stacker crane transports only one pallet at a time with the tchebychev travel, I/O point is located at the cornor of the rack, and items are stored by the class-based storage assignment rule. In this study, the racks are treated as the continuous rectangle in time and a statistical approach was used to develop the models. In order to test the proposed models, average travel times determined by the models are compared with the true values for various rack shapes.