• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.157-168
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• 2006

Spatial detection system such as AVI, GPS, and Beacon etc. can provide spatial travel time only after a vehicle Passes through a road section. In this context, majority of the existing studies on the link travel time estimation area has focused on the arrival time-based link travel time estimation. rather than departure time-based link travel time estimation. Even if some of the researches on this area have developed departure time-based link travel time estimation algorithms, they are limited in that they are not applicable in a real-time mode. The objective of this study is to develop an departure time-based link travel time estimation algorithm which is applicable in a real-tine mode. Firstly, this study discussed the tradeoff between accuracy and timeliness of the departure time-based on-line link travel time estimates. Secondly, this study developed an departure time-based on-line link travel time estimation algorithm which utilizes the Baysian inference logic. It was found that the proposed approach could estimate departure time-based link travel times in a real-time context with an acceptable accuracy and timeliness.

• 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.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.23 no.6 s.84
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• pp.19-30
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• 2005

The objective of this research is to keep track of path travel time using methods of collecting traffic data. Users of traffic information are looking for extensive information on path travel time, which is referred to as the time taken for traveling from the origin to the destination. However, all the information available is the average path travel times, which is a simple sum of the average link travel times. The average path travel time services are not up to the expectation of traffic information consumers. To improve provide more accurate path travel time services, this research makes a number of different estimates of various path travel times on one path, assuming it will be under the same condition, and provides a range of estimates with their probabilities to the consumers, who are looking for detailed information. To estimate the distribution of the path travel times as a combination of link travel times. this research analyzes the relation between the link travel time and path travel time. Based on the result of the estimation. this research develops the algorithm that combines the distribution of link travel time and estimates the path travel time based on the link travel times. This algorithm was tested and proven to be highly reliable for estimating the path traffic time.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.739-746
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• 2006

The bus probe-based link travel times were more readily available due to bus' fixed route schedule and it was different from that of taxi-based one in its value for the same link. At the same time, the bus-based one showed less accurate information than the taxi-based link travel time, in terms of reliability expressed by 1-RMSE(%) measure. The purpose of this thesis is to develop a heuristic algorithm for mixing both sources-based link travel times. The algorithm used both real-time and historical profile travel times. Real-time source used 4 consecutive periods' average and historical source used average value of link travel time for various congestion levels. The algorithm was evaluated for Seoul urban arterial network 3 corridors and 20 links. The results based on the developed algorithm were superior than the mere fusion based link travel times and the reliability amounted up to 71.45%. Some limitation and future research agenda have also been discussed.

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.145-154
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• 2008

The purpose of this study is to evaluate the quality of on-line departure time-based link travel time estimates. For this, accuracy (i.e. estimation error) and timeliness (i.e. degree of time lag) are proposed as MOE of the quality of on-line link travel time estimates. Then the relationship between quality of link travel time estimates and link length and level of congestion is analyzed. It was found that there is trade-off between the accuracy and timeliness of link travel time estimates. The estimation error was modeled to consist of two components: one is systematic error and the other is mean square error which reflects level of congestion. further, time lag was again segmented into three parts for the analysis purpose. There are minimum one, congestion-related one, and update interval-related one. From the real-world data using AVI system, it was revealed that regardless of the link length and level of congestion, 10 minutes of time lag occurs in general.

• Journal of Korean Society of Transportation
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• v.25 no.2 s.95
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• pp.145-155
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• 2007

The objectives of this study aye to develop an on-line departure time-based travel time estimation method and to determine an optimal link length for the estimation. This study developed a link-based rolling horizon logic as the travel time estimation method. In order to determine an optimal link length, the information error of the travel time provision from the user's perspective was defined and employed as a selection criterion. It was found that, when the travel time aggregation size was set as five minutes, a link length of four kilometers gave the most accurate result.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.2
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• pp.15-25
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• 2007

This paper aims at testing the applicability of RFID (radio frequency identification) based link travel time estimation algorithm in urban street settings in Jeju island Korea. For this, we developed algorithm and compared link travel times derived from the RFID probe based algorithm with those from (already available) GPS based link travel time estimation algorithm and with the actual link travel times from survey. RFID readers are composed of master reader and slave reader and the participating passenger cars were supposed to be equipped with RFID tag inside the vehicle. The data were sent to traffic information center and we used those data in comparison. The algorithm produced link travel times in a successful manner and the accuracy of those link travel times was about 88%. For the same link segments, the accuracy of GPS based link travel times was 93%. The t-test showed that both RFID and GPS based link travel times were not different in accuracy from statistical point of view. The applicability of RFID was tested successfully and the algorithm proposed seemed to be used in similar urban settings. Some limits and future research agenda have also been presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.1 no.1
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• pp.41-51
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• 2002

As Advanced Traveler Information System(ATIS) is the kernel of the Intelligent Transportation System, it is very important how to manage data from traffic information collectors on a road and have at borough grip of the travel time's change quickly and exactly for doing its part. Link travel time can be obtained by two method. One is measured by area detection systems and the other is estimated by point detection systems. Measured travel time by area detection systems has the limitation for real time information because it Is calculated by the probe which has already passed through the link. Estimated travel time by point detection systems is calculated by the data on the same time of each. section, this is, it use the characteristic of the various cars of each section to estimate travel time. For this reason, it has the difference with real travel time. In this study, Artificial Neural Networks is used for estimating link travel time concerned about the relationship with vehicle detector data and link travel time. The method of estimating link travel time are classified according to the kind of input data and the Absolute value of error between the estimated and the real are distributed within 5$\~$15minute over 90 percent with the result of testing the method using the vehicle detector data and AVI data of Namsan Tunnel $\#$1. It also reduces Time lag of the information offered time and draws late delay generation and dissolution.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.241-246
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• 2010

This study is to estimate the link travel time of road networks in urban areas utilizing traffic information which is collected throughout the operation of Bus Information System (BIS). BIS, which applies the hightech information technology to an existing bus system, has been developing and operating in many bodies including the local self-government entities. However, a study to consider the technology trend is relatively rare. Even though some useful traffic informations have been collected throughout the operation of an existing BIS, which set limits to the development of a future service of integrated analysis. Accordingly, in this study, a fundamental research is performed for traffic controls in urban areas and providing a traffic information for driver throughout the estimation of link travel time of road networks. The study is proceeded throughout the data collected from the operation of BIS (Bus Information System). The result showed that the patterns of going through traffic were divided up to 2 in the bus travel time in BIS then estimate two link travel time.