• Title/Summary/Keyword: Travel pattern

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An Activity-Based Analysis of Heavy-Vehicle Trip Chains (우리나라 대형 화물차의 통행사슬 분석:활동기반모형 적용)

  • Joh, Chang-Hyeon;Kim, Chan-Sung;Seong, Hong-Mo
    • 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.

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Analysis and Estimation of Factors Affecting Travel Time Budget (통행시간예산의 요인분석 및 추정)

  • Kim, Tae-Ho;Park, Je-Jin;Lee, Ki-Young;Park, Yong-Duk
    • International Journal of Highway Engineering
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    • v.11 no.3
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    • pp.13-21
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    • 2009
  • The traveler's travel pattern has significantly changed due to the social and economic changes. The travel time among the traveler's pattern is the limited resource. The travelers are trying to maximize the utility of travel with the least travel cost. So, the travelers travel with their own travel time budget in mind, which they can pay or choose to pay for the optimal maximization of the utility of the individuals. This research is to group and extract the specific factors which affect the travel time budget by utilizing the CART analysis method, which enables the analysis of traveler's characteristics and their interrelationship based on the data collected from "2002 Household Travel Practice Research" and then try to derive a model for estimating the traveler’s travel time budget. The result of CART analysis shows that the factors which affect the travel time budget include the traveler's age, size of house, type of house, type of employment, job and relation to the head of household. Considering the affecting factors derived, I developed an estimation model. From that model, we found that the age, size of house and type of house were positively (+) related to the travel time budget while the homeworking people who have less travel frequency as a type of employment were negatively (-) related to it. In particular, from the point of type of job, the housewives, children not yet old enough to attend schools and people who are working in the agricultural, or marine product industries were found to have the negative (-) value while the people who have the administrative, office, management jobs were found to have the positive (+) value.

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Measurement of Travel Time Using Sequence Pattern of Vehicles (차종 시퀀스 패턴을 이용한 구간통행시간 계측)

  • Lim, Joong-Seon;Choi, Gyung-Hyun;Oh, Kyu-Sam;Park, Jong-Hun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.7 no.5
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    • pp.53-63
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    • 2008
  • In this paper, we propose the regional travel time measurement algorithm using the sequence pattern matching to the type of vehicles between the origin of the region and the end of the region, that could be able to overcome the limit of conventional method such as Probe Car Method or AVI Method by License Plate Recognition. This algorithm recognizes the vehicles as a sequence group with a definite length, and measures the regional travel time by searching the sequence of the origin which is the most highly similar to the sequence of the end. According to the assumption of similarity cost function, there are proposed three types of algorithm, and it will be able to estimate the average travel time that is the most adequate to the information providing period by eliminating the abnormal value caused by inflow and outflow of vehicles. In the result of computer simulation by the length of region, the number of passing cars, the length of sequence, and the average maximum error rate are measured within 3.46%, which means that this algorithm is verified for its superior performance.

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Travel Behavior Analysis of KTX Commuter Belt (KTX 통근권역의 통행행태 분석)

  • Lee, Jin-Sun;Kim, Kyoung-Tae
    • Journal of the Korean Society for Railway
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    • v.11 no.4
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    • pp.417-423
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    • 2008
  • Transportation planners are increasingly adopting policies aimed at changing travel choices made by general commuter. Theories on the relationship between high-speed technology and transport address changes in travel behavior of regional commuter due to alterations in the Kyung-Bu railroad transportation corridor. The purpose of this paper is to examine the relationships between travel behavior and high-speed technology. The KORAIL data allows us to explore the differences between travel characteristics that are usually hard to discern by guesswork. The effects of travel time were found to be significant in the full decisions that control for commuting KTX. Although many argue that transportation behavior cannot be changed, this paper demonstrates that about 4 years of behavioral data on KTX travel show otherwise. In this paper we explore several possibilities to fill in some of the gaps in our knowledge on the expansion of commuter belt.

Analysis of Runoff Effect of Drainage System at Urban Watershed due to Urbanization (도시화에 따른 도시유역 배수계통의 유출영향분석에 관한 연구)

  • Seo, Kyu Woo;Heo, Jun Haeng;Cho, Won Cheol
    • Journal of Korean Society of Water and Wastewater
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    • v.11 no.4
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    • pp.80-90
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    • 1997
  • The ILLUDAS and SWMM models were applied to the developing area of Dongsucheon for comparisons of the total runoff, peak discharge and travel time. For this purpose, the present and future urbanization rates were assumed 70% and 90%, respectively. The runoff analysis of two models has been performed based on 10, 20, 30 and 50 return periods and Huff's 4 quantiles for time distribution pattern of design rainfalls. As results, the total runoff based on Huff's pattern had an decreasing order of 1, 4, 3 and 2 quantiles for both models. The SWMM model showed that there were 4.3% increasing of the total runoff, 4.9% increasing of peak discharge, and 6.6% decreasing of travel time. Similarly, for ILLUDAS model, there were 7.3% and 9.2% increasing of total runoff and peak discharge, respectively and 9.1% decreasing of travel time.

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Analysis Period of Input Data for Improving the Prediction Accuracy of Express-Bus Travel Times (고속버스 통행시간 예측의 정확도 제고를 위한 입력자료 분석기간 선정 연구)

  • Nam, Seung-Tae;Yun, Ilsoo;Lee, Choul-Ki;Oh, Young-Tae;Choi, Yun-Taik;Kwon, Kenan
    • International Journal of Highway Engineering
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    • v.16 no.5
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    • pp.99-108
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    • 2014
  • PURPOSES : The travel times of expressway buses have been estimated using the travel time data between entrance tollgates and exit tollgates, which are produced by the Toll Collections System (TCS). However, the travel time data from TCS has a few critical problems. For example, the travel time data include the travel times of trucks as well as those of buses. Therefore, the travel time estimation of expressway buses using TCS data may be implicitly and explicitly incorrect. The goal of this study is to improve the accuracy of the expressway bus travel time estimation using DSRC-based travel time by identifying the appropriate analysis period of input data. METHODS : All expressway buses are equipped with the Hi-Pass transponders so that the travel times of only expressway buses can be extracted now using DSRC. Thus, this study analyzed the operational characteristics as well as travel time patterns of the expressway buses operating between Seoul and Dajeon. And then, this study determined the most appropriate analysis period of input data for the expressway bus travel time estimation model in order to improve the accuracy of the model. RESULTS : As a result of feasibility analysis according to the analysis period, overall MAPE values were found to be similar. However, the MAPE values of the cases using similar volume patterns outperformed other cases. CONCLUSIONS : The best input period was that of the case which uses the travel time pattern of the days whose total expressway traffic volumes are similar to that of one day before the day during which the travel times of expressway buses must be estimated.

A study on the User Satisfaction of Travel behavior (관광지 선택행동에 따른 만족도에 관한 연구)

  • 박신자
    • Journal of Applied Tourism Food and Beverage Management and Research
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    • v.10
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    • pp.139-158
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    • 1999
  • This study is concerned with analysis of user satisfaction for travel behavior. It is aimed at investigating the socioeconomic characteristics, motivation, and use pattern of the visitors at tour. For tourists' perception and preference analysis, multi-dimensional scaling was used. It is left that this type of marketing analysis of tourism and travel offers great potentional for those concerned with the developement and management of tourist vacation areas. First, the study demanstrated clearly that different tourist and portential visitors to a tourist area seek different benefit bundles from their vacation in a particular tourist areas. Second, it demonstrated that a benefit segmentation approach to tourism and travel would be the most effective that the demographic segmentation approach usually pursued in the tourism and travel industry. Form a methodological viewpoint, it has demonstrated an application of multidimensional scaling techniques to marketing in an important industry.

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Understanding elderly's travel pattern based on individual trip trajectory using smart card data (스마트카드 데이터를 활용한 통행궤적 기반 고령인구 통행유형 분류)

  • Lee, Ju-Yoon;Kang, Young-Ok
    • Journal of Cadastre & Land InformatiX
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    • v.52 no.2
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    • pp.153-169
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    • 2022
  • With the extension of the average life span and the rapid aging of the population, defining elderly population as a single group is difficult as the physical, economic and social conditions of individual have become different. Therefore, policies that take into account the characteristics of each group are required. The purpose of this study is to classify individual travel types and to analyze the characteristics of each travel type, based on individual public transportation trajectory data as known as smart card data. Among the four classified types, the long-distance low-frequency stay type and the short-range medium-frequency mobile type show external activity traffic characteristics for retirement leisure, while the long-distance high-frequency stay type and the long-distance high-frequency mobile group include regular commuting. Traffic variability and residence areas of stay were identified in terms of each classified travel type. The results of this study provide the important suggestions for establishing a transportation policy that takes into account the characteristics of each type of elderly population in Seoul.

Analysis of the Elderly Travel Characteristics and Travel Behavior with Daily Activity Schedules (the Case of Seoul, Korea) (활동 스케줄 분석을 통한 고령자의 통행특성과 통행행태에 관한 연구)

  • Seo, Sang-Eon;Jeong, Jin-Hyeok;Kim, Sun-Gwan
    • Journal of Korean Society of Transportation
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    • v.24 no.5 s.91
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    • pp.89-108
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    • 2006
  • Korea has been entering the ageing society as the population of age over 65 shared over 7% since the year 2000. The ageing society needs to have transportation facility considering elderly people's travel behavior. This study aims to understand the elderly people's travel behavior using recent data in Korea. The activity schedule approach begins with travel outcomes are part of an activitv scheduling decision. For tho?e approach. used discrete choice models (especially. Nested Logit Model) to address the basic modeling problem capturing decision interaction among the many choice dimensions of the immense activity schedule choice set The day activity schedule is viewed as a sot of tours and at-home activity episodes tied togather with overarching day activity pattern using the Seoul Metropolitan Area Transportation Survey data, which was conducted in June, 2002. Decisions about a specific tour in the schedule are conditioned by the choice of day activity pattern. The day activity scheduling model estimated in this study consists of tours interrelated in a day activity pattern. The day activity pattern model represents the basic decision of activity participation and priorities and places each activity in a configuration of tours and at-home episodes. Each pattern alternative is defined by the primary activity of the day, whether the primary activity occurs at home or away, and the type of tour for the primary activity. In travel mode choice of the elderly and non-workers, especially, travel cost was found to be important in understanding interpersonal variations in mode choice behavior though, travel time was found to be less important factor in choosing travel mode. In addition, although, generally, the elderly was likely to choose transit mode, private mode was preferred for the elderly over 75 years old owing to weakened physical health for such things as going up and down of stairs. Therefore. as entering the ageing society, transit mode should be invested heavily in transportation facility Planning tor improving elderly transportation service. Although the model has not yet been validated in before-and-after prediction studies. this study gives strong evidence of its behavioral soundness, current practicality. and potential for improving reliability of transportation Projects superior to those of the best existing systems in Korea.

A Study on Development of Bus Arrival Time Prediction Algorithm by using Travel Time Pattern Recognition (통행시간 패턴인식형 버스도착시간 예측 알고리즘 개발 연구)

  • Chang, Hyunho;Yoon, Byoungjo;Lee, Jinsoo
    • 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.