• 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

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.1115-1122
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• 2013

Recently the demands for traffic information tend to increase, and travel time might one of the most important traffic information. To effectively estimate exact travel time, highly reliable traffic data collection is required. BIS(Bus Information System) data would be useful for the estimation of the route travel time because BIS is collecting data for the bus travel time on the main road of the city on real-time basis. Traditionally use of BIS data has been limited to the realm of bus operating but it has not been used for a variety of traffic categories. Therefore, this study estimates a route travel time on road networks in urban areas on the basis of real-time data of BIS and then eventually constructs regression models. These models use an explanatory variable that corresponds to bus travel time excluding service time at the bus stop. The results show that the coefficient of determination for the constructed regression model is more than 0.950. As a result of T-test performance with assistance from collected data and estimated model values, it is likely that the model is statistically significant with a confidence level of 95%. It is generally found that the estimation for the exact travel time on real-time basis is plausible if the BIS data is used.

• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.257-272
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• 2013

As visiting of Chinese tourists to Korea have increased gradually, Chinese people who use online travel reservation services for their visits to Korea have increased accordingly. In addition, the growth of the online reservation services in China is very rapid. Therefore, it is necessary to study the factors affecting the Chinese tourists' intention to use the online travel reservation services in order to advance e-business in the travel industry. This paper presents a new research model based on Technology Acceptance Model (TAM) including perceived risk, service factors, online reviews and user satisfaction. Also, it analyzes factors affecting the Chinese tourists' intention to use the online travel reservation services. The results of this study show that the key influencers of the online travel reservation services are perceived usefulness, perceived ease, and perceived risk. Additionally, based on these results, this paper proposes practical suggestions to solve the existing problems and improve online travel reservation websites in China.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.2
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• pp.192-202
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• 2008

Typical activity-based travel analysis has been focused on passenger travel using household survey data. The current research focuses on freight transport using one-day travel survey data. Passenger travel can be seen as the outcome of traveller's subjective decision-making, whereas freight transport is the outcome of shipper or transport company's optimized scheduling. The research conducts an activity-based analysis of freight-vehicle trip chains. In particular, the research focuses on the difference in travel pattern between shipper-oriented private vehicle and transport company-oriented business vehicle. The research analyzed the travel diary of freight vehicles collected as part of the third national logistic survey in 2005. The diary is freight driver's one-day travel record including the information of loading capacity, item transported, destination, arrival time, etc. The analysis results show the difference between private and business vehicles in the travel pattern regarding the sequences of destination, destination type and item transported and the multi-dimensional information of the three sequences.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.117-125
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• 2022

Recently, as users' interest for travel increases, research on a travel route recommendation service that replaces the cumbersome task of planning a travel itinerary with automatic scheduling has been actively conducted. The most important and common goal of the itinerary recommendations is to provide the shortest route including popular tour spots near the travel destination. A number of existing studies focused on providing personalized travel schedules, where there was a problem that a survey was required when there were no travel route histories or SNS reviews of users. In addition, implementation issues that need to be considered when calculating the shortest path were not clearly pointed out. Regarding this, this paper presents a quantified method to find out popular tourist destinations using social big data, and discusses problems that may occur when applying the shortest path algorithm and a heuristic algorithm to solve it. To verify the proposed method, 63,000 places information was collected from the Gyeongnam province and big data analysis was performed for the places, and it was confirmed through experiments that the proposed heuristic scheduling algorithm can provide a timely response over the real data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1851-1861
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• 2014

This study aims to calculate reliable sectional travel speeds with the consideration of the characteristics of the probe data collected in the interrupted traffic flow. First, in order to analysis the characteristics of the probe data, we looked into the distribution of the sectional travel times of each probe vehicle and compared the difference in the sectional travel speeds of each probe vehicle collected by DSRC. As a result, it is shown that outliers should be removed for the distribution of the sectional travel times. However, The comparison results show that the sectional travel speeds from the DSRC probe vehicles are not significantly different. Finally, based on the distribution characteristics of the sectional travel speeds of each probe vehicle and the representative values counted during a collection period, we drew the optimal outlier removal procedure and evaluated the estimation errors. The evaluation results showed that the DSRC sectional travel speeds were found to be similar to the observed values from actually running vehicles. On the contrary, in the case of the sectional travel speeds of intra-city bus, it was analyzed that they were less accurate than the DSRC sectional travel speeds. In the future, it will be necessary to improve BIS process and make use of the travel information on intra-city buses collected in real time to find various ways of applying it as traffic information.

• Knowledge Management Research
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• v.15 no.1
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• pp.45-63
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• 2014

Due to advance in Internet technology, most tourists tend to search travel information in the Online Travel Communities(OTC). Given this new paradigm in terms of finding travel information, most of relevant studies in this area are still dealt with explaining tourists' behaviors regardless of the types of communications. Therefore, to overcome some limitations in previous studies, we attempt to examine the relationships between both formal and informal communications and tourists' behavioral changes in the OTC context. Specifically, we developed a research model by employing the PPM(push-pull-mooring) framework and tested it to understand why and how tourists' behaviors might be changed. Survey data collected from 323 online tourists were used to test the model the model using SEM(structural equation modeling). The implications of our empirical findings for both research and practice are discussed.

• Journal of Korean Society of Transportation
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• v.14 no.4
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• pp.107-129
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• 1996

Recently, surveillance system designed to collect various trsffic information are becoming new areas of development . Among these, the image detector is a ayatem which can measure the travel time and speed in realtime and this is emerging as the most effcient tool to be available in future related areas. But in measuring wide-area information in realtime, the image detector are yet full of problem in its accuracy. The aim of this ahesis is to develop an algorithms which can collect wide-area information such as travel time and travel speed in urban networks and freeways in realtime. The information on wide-area such as travel time and travel speed is important in accomplishing strategic function in traffic control. The algorithm developed from this study is based on the image tracking model which tracks a moving vehicle form image datas collected continuously, and is constructed to perform realtime measurement. To evaluate the performance of the developed algorithms, 600 ind vidual vehicles in total were used as data for the study, and this evaluation was carried out with the differenciation of day and night condition at the access roads in front of AJou University, In the statistical analysis results, the error rate was recorded as 5.69% and it has proved to be applicable on the field in both day and noght conditions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.101-108
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• 2003

When drivers encounter multiple available routes, they may evaluate the utility of each route. Two important factors in the evaluation are travel time and travel cost. Without hewing the current travel time of each route, drivers' decisions are not necessarily optimum. It is called 'transparency issue' that drivers are blinded to choose the optimum route among the others because of the limited travel time information. As a result of this, competing route travel times tend to fluctuate. This case study to utilize the data of Namsan traffic information system confirms that this travel time fluctuation can be lessened as real time traffic information is provided.