• Environmental and Resource Economics Review
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• v.30 no.2
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• pp.207-235
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• 2021

This paper examines the effects of ambient air pollution by ozone and particulate matter on traveling by mode of transport. We estimate the SUR model of travel time by different modes of transportation using individual level data of travel diaries. We find that, as air pollution levels rises, traveling by privately-owned vehicles increases but traveling by bus decreases. Our results also show that, when an air quality alert is issued, bus traveling increases in an effort to reduce pollution levels, but traveling by own car does not change and traveling by train declines. This suggests that alert programs may not be highly effective in reducing air pollution emissions from vehicles because voluntary switching to public transportation induced by air quality alerts is outweighed by individual effort of avoiding exposure to pollution.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.101-111
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• 2017

This study propose a method to predict the bus arrival time by considering the signal delay time which is an element which can not be considered in the current bus arrival prediction information generation algorithm. In order to consider the signal delay time, travel time is divided into three components: service time, cruising travel time, and signal delay time. Signal delay time was estimated using intersection arrival time and TOD. The results show that most of the errors that occurred in predicting the arrival time are within about 30 seconds. Some of the estimates have large errors due to the nature of this methodology that uses the estimated value of the intersection arrival time rather than the observation value. It is also difficult to predict the arrival time of the express buses using this method. Future studies such as improving this through real-time location information will greatly improve the accuracy of the methodology.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.481-498
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• 2017

Travel time reduction benefit is the most important benefit item in the feasibility study of transportation infrastructure investment projects and calculated by using the value of travel time. The current feasibility study guideline (5th edition) calculate the value of non-business ravel time in a metropolitan area, using the ratio of the value of non-business travel time to business travel time calculated based on the nationwide inter-regional traffic survey data of 1999. The characteristics of metropolitan trips are different from those of nationwide regional trips. Metropolitan trips have frequent transfers between multiple public transits and long-time commuter trips. Therefore, this research aims to calculate the value of travel time reflecting traffic characteristics in a metropolitan area by improving the limitation of current calculation methods. To reflect these characteristics, this research extracts commuter trips from non-business trips and calculates the value of travel time for commuter trips. The results of the likelihood ratio test for the commuter trip model and the non-business trip model are found to be statistically significant. An integrated public transportation model was also estimated in this study to reflect the trip conditions of the Seoul metropolitan area integrated fare system. The results of comparing coefficients between bus and subway in the integrated public transit model indicated that there were no statistically significant differences between the two modes.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.8 no.1
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• pp.25-32
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• 1988

Vehicle platoons starting a stopline are dispersed while travelling along the street and the delay at the next intersection depends on the arrival pattern of dispersed traffic flow. In this paper, the platoon dispersion charactiristics of our country, especially the time gap between passenger cars and buses caused by the dwell time at bus stops, were investigated through travel time surveys. Based on the survey results, on improved analysis method of intersection delay is proposed.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1811-1825
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• 2011

This study analyzed the transit services with respect to transit service measures such as the load factor representing number of passengers between stops, dwelling time, and operational speed based on transit smart card data recorded in 2009. A case study on the local bus line 7024 connecting Seoul railway station to evaluate bus services at passenger perspectives was accomplished. From the results, we found that the dwelling time was not affected by the number of passengers which is because the tagging patterns are different among passengers. The operational speed was analyzed by calculating the average speed of the bus route and the speed of each bus stops based on dwelling time. Interestingly, calculating operation speed based on the transit smart card data is the first time effort ever made and this means that it is not necessary to observe travel speed of bus and railway at a field level any more. we hope that this study will be a basis of evaluation of transit services purely based on the transit smart card data and help to make better transit services for passengers and operators as well.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.223-229
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• 2010

The bus transfer system has been extended from Seoul to Gyonggi province to provide better Seoul metropolitan area transit service in September, 2008. Moreover, the curved bus routes, except existing rapid bus routes, which cause longer travel time have been straightened out. Also, the Skip Stop operation suggested by passengers has been introduced to main stops in the newly added express bus lines. This study surveyed passengers service satisfaction for the recent adopted bus policies such as the transfer discount system and the express bus system in Seoul Metropolitan area. The survey results may be important foundation for future strategies for improvement. The survey included questionnaires about the importance and the satisfaction level on both quantitative and qualitative factors. The results were statistically analyzed by the modified IPA (Importance-Performance Analysis). As the result of the survey, the newly adopted services such as fare system, fare discount on transferring, travel time savings and increased number of stops are economically feasible and satisfactory, whereas the accessibility to stops, ventilation and air quality in vehicles are the priorities to be improved. Also, the safety and the information system is in need of improvement.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.5
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• pp.87-97
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• 2013

This study tried to explore the quantitative travel heterogeneity between elderly and non elderly people, focusing on urban and rural areas in south Chungcheong province. For the analysis, a PLS(Partial least square) model is applied with economic and traffic environment characteristics of the urban and rural areas. The characteristics of elderly and non elderly people in the urban and rural areas are derived from the 2011 person trip survey. As a result, the study found out that the key factors affect on elderly people in the urban and rural areas are bus operation interval, number of bus operation routes, number of household member, and a monthly average income of household. In case of non elderly people, areas economic factors such as GRDP, the rate of economic activity, and employment status as well as those of elderly people. Meanwhile, female elderly people in rural area have more sensitivity compared to male elderly people and the gender heterogeneity is not revealed in non elderly people.

• Journal of Korean Society of Transportation
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• v.31 no.4
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• pp.47-57
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• 2013

This study aims at analyzing transportation equity between geographical areas of Gyonggi Province, by taking both the transportation infrastructure and travel behavior into account. Indicators of transportation infrastructure include the indices of road infrastructure, transit infrastructure and regional characteristics. Travel behavior concerns information from bus card data on a survey day. The hot-spot analysis conducted included spatial cluster analysis and global/local regression analyses. The analysis results identified geographical areas of four different classes of transportation equity, from the area with high level infrastructure surrounded by the areas with high level infrastructure (HH) to the area with low level surrounded by the areas with low level (LL). The area of HH type showed big numbers of passengers, trips and transfers, whereas the area of LL type shows big figures of internal trip frequency, travel time, travel distance, travel speed and transit fare. Global regression analysis showed that number of passengers, number of transfers, number of internal trips and mean travel speed are important to the level of transportation infrastructure. GWR with these four significant variables significantly improved the AICs and ANOVA results, which implies that the infrastructure is likely explained by travel characteristics differently between geographical areas in Gyonggi Province.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.42-52
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• 2022

Bus Information System (BIS) services are expanding nationwide to small and medium-sized cities, including large cities, and user satisfaction is continuously improving. In addition, technology development related to improving reliability of bus arrival time and improvement research to minimize errors continue, and above all, the importance of information accuracy is emerging. In this study, accuracy performance was evaluated using LSTM, a machine learning method, and compared with existing methodologies such as Kalman filter and neural network. As a result of analyzing the standard error for the actual travel time and predicted values, it was analyzed that the LSTM machine learning method has about 1% higher accuracy and the standard error is about 10 seconds lower than the existing algorithm. On the other hand, 109 out of 162 sections (67.3%) were analyzed to be excellent, indicating that the LSTM method was not entirely excellent. It is judged that further improved accuracy prediction will be possible when algorithms are fused through section characteristic analysis.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.7
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• pp.297-306
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• 2017

Citizens want more accurate forecast information using Bus Information System. However, most bus information systems that use an average based short-term prediction algorithm include many errors because they do not consider the effects of the traffic flow, signal period, and halting time. In this paper, we try to improve the precision of forecast information by analyzing the influencing factors of the error, thereby making the convenience of the citizens. We analyzed the influence factors of the error using BIS data. It is shown in the analyzed data that the effects of the time characteristics and geographical conditions are mixed, and that effects on halting time and passes speed is different. Therefore, the halt time is constructed using Generalized Additive Model with explanatory variable such as hour, GPS coordinate and number of routes, and we used Hidden Markov Model to construct a pattern considering the influence of traffic flow on the unit section. As a result of the pattern construction, accurate real-time forecasting and long-term prediction of route travel time were possible. Finally, it is shown that this model is suitable for travel time prediction through statistical test between observed data and predicted data. As a result of this paper, we can provide more precise forecast information to the citizens, and we think that long-term forecasting can play an important role in decision making such as route scheduling.