• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.617-631
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• 2019

In the four-step demand model, a gravity mode is used most commonly at the trip distribution stage. The purpose of this study was to develop a new friction factor that can express the accessibility property as a single friction factor to compensate for the variable limits of the gravity model parameters (travel time, travel cost). To derive a new friction factor, a new friction factor was derived using the space syntax that can quantify the characteristics of the urban space structure, deriving the link-unit integration degree and then using the travel time and travel distance relationship. Calibration of the derived friction factor resulted in a similar level to that of the existing friction factor. As a result of verifying the various indicators, the explanatory power was found to be excellent in the short - and long - distance range. Therefore, it is possible to derive and apply the new friction factor using the integration index, which can complement the accessibility beyond the limit of the existing shortest distance, and it is believed to be more advantageous in future utilization.

• Journal of the Korean Geographical Society
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• v.35 no.4
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• pp.585-598
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• 2000

본 연구를 통하여 대형할인점 이용자, 재래시장 이용자, 그리고 수퍼마켓 이용자들의 각 쇼핑장소를 중심으로 한 거주지역 공간적 분포 및 쇼핑패턴의 차이를 비교한 결과. 이 세종류의 쇼핑장소 이용자들간의 각 쇼핑장소들 중심으로 한 거주지역 분포의 공간적 패턴 및 쇼핑통행 패턴은 상당한 차이를 나타내고 있다. 또한 대형할인점을 이용자를 제외한 재래시장 이용자와 슈퍼마켓 이용자들을 대상으로 그들이 이용하기를 원하는 대형할인점의 이용을 제한하는 주요 요인을 분석한 결과 통행거리, 운전면허 미소지, 자가용 승용차 미보유 등 대형할인점으로의 접근을 위한 과정에서 발생하는 제약 요인들이 가장 큰 비중을 차지하고 있는 것으로 나타난다. 이러한 점들을 볼 때, 재래시장 및 수퍼마켓이 주민들의 일상적인 쇼핑장소의 역할을 할 때와는 달리 대형할인점의 등장은 이곳으로의 주민들의 접근능력의 차이에 따라 주민들간 일상적 소비장소의 차별화가 진행될 수 있음을 시사한다. 특히 최근 대형할인점의 입지가 가속화되고 이에 따라 재래시장 및 수퍼마켓의 기능이 쇠퇴하고 있음을 고려할 때, 신체적 그리고 사회경제적 특성의 차이에 따라 대형할인점으로의 접근에 제한을 받는 주민들의 일상적 소비공간은 더욱 위축되고 고립될 가능성이 있다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.141-156
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• 2023

This study aims to improve understanding of freight movement, crucial for logistics facility investment and policy making. It addresses the limitations of traditional freight truck traffic data, aggregated only at city and county levels, by developing a new methodology. This method uses trip chain data for more detailed, facility-level analysis of freight truck movements. It employs DTG (Digital Tachograph) data to identify individual truck visit locations and creates H3 system-based polygons to represent these visits spatially. The study also involves an algorithm to dynamically determine the optimal spatial resolution of these polygons. Tested nationally, the approach resulted in polygons with 81.26% spatial fit and 14.8% error rate, offering insights into freight characteristics and enabling clustering based on traffic chain characteristics of freight trucks and visited facility types.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.2
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• pp.1-11
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• 2014

In this paper, travel speed patterns were deducted based on historical DSRC travel speed data using Decision Tree technique to improve availability of the massive amount of historical data. These patterns were designed to reflect spatio-temporal vicissitudes in reality by generating pattern units classified by months, time of day, and highway sections. The study area was from Seoul TG to Ansung IC sections on Gyung-bu highway where high peak time of day frequently occurs in South Korea. Decision Tree technique was applied to categorize travel speed according to day of week. As a result, five different pattern groups were generated: (Mon)(Tue Wed Thu)(Fri)(Sat)(Sun). Statistical verification was conducted to prove the validity of patterns on nine different highway sections, and the accuracy of fitting was found to be 93%. To reduce travel pattern errors against individual travel speed data, inclusion of four additional variables were also tested. Among those variables, 'traffic condition on previous month' variable improved the pattern grouping accuracy by reducing 50% of speed variance in the decision tree model developed.

• 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.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.163-174
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• 2008

The conventional four-step travel demand model is still widely used as the state-of-practice in most transportation planning agencies even though it does not provide reliable estimates of travel demand. In order to improve the accuracy of travel demand estimation, implementing an alternative approach would be critical as much as acquiring reliable socioeconomic and travel data. Recently, the role of travel demand model is diverse to satisfy the needs of microscopic analysis regarding various policies of travel demand management and traffic operations. In this context, the activity-based approach for travel demand estimation is introduced and a case study of developing a spatial-temporal activity presence-based approach that estimates travel demand through forecasting number of people present at certain place and time is accomplished. Results show that the spatial-temporal activity presence-based approach provides reliable estimates of both number of people present and trips actually people made. It is expected that the proposed approach will provide better estimates and be used in not only long-term transport plans but short-term transport impact studies with respect to various transport policies. Finally, in order to introduce the spatial-temporal activity presence-based approach, the data such as activity-based travel diary and land use based on geographic information system are essential.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.177-185
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• 2002

본 논문의 목적은 링크통행시간 자료를 수집하는 시스템에서 소요 프로브차량대수에 영향을 주는 요소들을 규명하고. 최적의 소요 프로브차량대수를 결정하는 모형을 개발하는데 있다. 자가용승용차, 택시, 버스, 택배차량 등 여러 종류의 차량들이 프로브차량으로 사용될 수 있다. 그러나 일정한 정확도 이상의 교통정보를 수집하기 위해서 얼마나 많은 프로브차량이 필요한지에 대한 연구는 그다지 깊이 있게 이루어지지 않았다. 적정 소요 프로브차량대수는 링크통행시간 자료수집 기술 수집대상 링크의 공간적 범위, 프로브차량의 종류 및 운행 특성, 자료수집 시스템의 신뢰도, 수집되는 자료의 정확도 등에 영향을 받게 된다. 소요 프로브차량대수를 결정하는 링크당 평균 통행시간 자료수, 프로브차량 밀도의 최소 확률, 그리고 자료 미수집링크의 허용비율의 3가지 결정기준이 정의되었다. 또한 이러한 결정기준에 대해 소요 프로브차량대수를 산출하는 모형이 개발되었다. 일반적으로 주기당, 링크당 평균 필요 통행시간 자료수$(d_R)$, 단위길이당 프로브차량의 대수 또는 밀도$(n_{min} or {\alpha})$, 일정 프로브차량밀도 이상의 확률($\beta$), 그리고 자료 미수집링크의 비율($\gamma$)이 클수록 소요 프로브차량대수는 증가한다. 민간 교통정보회사의 통행시간 수집시스템에서 소요 프로브차량대수를 산정하는 사례연구가 수행되었으며, 여러가지 조건에서 소요 프로브차량대수가 산출되었다.

• Proceedings of the KGS Conference
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• 2003.11a
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• pp.144-148
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• 2003

1) 연구의 배경와 목적 정보통신기술의 비약적 발전은 공간이동에 있어서 '거리' 개념의 근본적인 변화를 가져오고 있다. 흔히 '시간에 의한 공간소멸' 또는 '시공간 압축'이라고 표현되는 그와 같은 변화는 일상적 생활공간에서뿐만 아니라 전지구적 범위에 이르기까지 장소와 장소, 지역과 지역 간에 발생하는 정보의 흐름을 실시간(real time)으로 연결한다. 그러나 정보통신기술의 발달이 장소와 장소, 지역과 지역 간에 발생하는 모든 통행을 대체하지는 못한다. (중략)

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.145-153
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• 2008

This study proposes a facility location model in consideration of spatial coverage and travel cost as an effort to make objective and effective decisions of natural gas filling stations. The proposed model is developed for fixed stations and consists of two stages. The first stage employs a heuristic algorithm to find a set of locations which satisfy the spatial coverage constraints determined by the maximum travel distance between the filling stations and bus depots. In the second stage, the optimal location of filling stations is determined based on the minimum travel cost estimated by using a modified transportation problem as well as the construction and maintenance costs of the filling stations. The applicability of the model is analyzed through finding the optimal location of filling stations for the city of Anyang, a typical medium-sized city in metropolitan Seoul, based on the demand of natural gas buses. This study is expected to help promote the spread of natural gas buses by providing a starting point of a objective and reasonable methodological perspective to address the filling station location problem.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.219-232
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• 2023

Mobility services need to change according to the regional characteristics of the target service area. Accordingly, analysis of mobility patterns and characteristics based on Origin-Destination (OD) data that reflect travel behaviors in the target service area is required. However, since conventional methods construct the OD data obtained from the administrative district-based zone system, it is hard to ensure spatial homogeneity. Hence, there are limitations in analyzing the inherent travel patterns of each mobility service, particularly for new mobility service like Demand Responsive Transit (DRT). Unlike the conventional approach, this study applies a data-driven clustering technique to conduct spatial analyses on OD travel patterns of regional mobility services based on reconstructed OD data derived from re-aggregation for original OD distributions. Based on the reconstructed OD data that contains information on the inherent feature vectors of the original OD data, the proposed method enables analysis of the spatial characteristics of regional mobility services, including public transit bus, taxi and DRT.