• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.86-98
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• 2018

Since 2015, the Korea Expressway Corporation has provided predicted travel time information, which is reproduced from DSRC systems over the extended expressway network in Korea. When it is open for public information, it helps travelers decide optimal routes while minimizing traffic congestions and travel cost. Although, sutiable evaluations to investigate the reliability of travel time forecast information have not been conducted so far. First of all, this study seeks to find out a measure of effectiveness to evaluate the reliability of travel time forecast via various literatures. Secondly, using the performance measurement, this study evaluates concurrent travel time forecast information in highway quantitatively and examines the forecast error by exploratory data analysis. It appears that most of highway lines provided reliable forecast information. However, we found significant over/under-forecast on a few links within several long lines and it turns out that such minor errors reduce overall reliability in travel time forecast of the corresponding highway lines. This study would help to build a priority for quality control of the travel time forecast information system, and highlight the importance of performing periodic and sustainable management for travel time forecast information.

• 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.

• Journal of Korean Society of Transportation
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• v.16 no.4
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• pp.153-166
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• 1998

본 연구에서는 도시 가로망에서의 구간 통행시간을 예측하기 위하여 time-frequency 분석의 일종인 웨이브렛변환과 RBF신경망 모형을 이용한 예측모형을 개발하였다. 웨이브렛 변환을 이용한 시계열 자료 분석을 통해서 통행시간에 내재되어 있는 다양한 패턴의 특징을 추출함으로써 오전/오후의 첨두현상, 신호교차로의 현시주기 등 주기적으로 발생되는 요인들에 의해서 통행시간 시계열 자료의 패턴에 나타나는 규칙성을 분석해 내었다. 분석된 패턴정보에 대한 규명은 카오스 이론을 근간으로한 시간지연좌표를 이용하여 시계열 자료의 규칙성을 시각적으로 판별하여 예측모형 구축에 활용하도록 하였다. 또, RBF신경망을 이용하여 예측범위의 공간적/시간적 확대에 따른 모형 구축에 소요되는 시간을 최소화하도록 하였으며, 시내버스 노선의 정류장간 운행시간 예측을 통해서 기존 연구에서 제기되었던 현실세계의 단순화, 다단계 예측시 정확성 등의 문제를 해결하였다. 예측실험결과 웨이브렛 변환을 데이터의 전처리 과정에 삽입하여 링크 통행시간의 패턴정보 예측에 활용할 경우, 기존의 예측모형에 비해서 훨씬 정확한 예측이 가능한 것으로 나타났으며, RBF 신경망은 짧은 학습시간에도 불구하고 역전파 신경망보다 우수한 예측력을 갖고 있는 것으로 밝혀졌다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.17-34
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• 2022

This paper develops a model for dynamic station assignment to optimize the Demand Responsive Transit (DRT) operation. In the process of optimization, we use the bus travel time as a variable for DRT management. In addition, walking time, waiting time, and delay due to detour to take other passengers (detour time) are added as optimization variables and entered for each DRT passenger. Based on a network around Anaheim, California, reserved origins and destinations of passengers are assigned to each demand responsive bus, using K-means clustering. We create a model for selecting the dynamic station and bus route and use Non-dominated Sorting Genetic Algorithm-III to analyze seven scenarios composed combination of the variables. The result of the study concluded that if the DRT operation is optimized for the DRT management, then the bus travel time and waiting time should be considered in the optimization. Moreover, it was concluded that the bus travel time, walking time, and detour time are required for the passenger.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.41-48
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• 2004

This research develops a model of participation and scheduling choice of urban leisure activity. A nested legit model was found to be an appropriate approach. Data collected from Deagu and Pohang City were used for empirical estimation of model parameters. The empirical results confirmed several behavioral aspects associated with participation and scheduling choice of urban leisure activity. The paper presents a discussion on implications that can be inferred from the empirical results. Finally, future potential research question are also discussed.

• Information and Communications Magazine
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• v.25 no.7
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• pp.10-15
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• 2008

최근 고속도로의 길이와 운전 차량 수가 빠른 속도로 증가하고 있어 운전자들에게 고속도로 교통상황를 신속하고 정확하게 제공하는 것이 중요한 문제로 대두되고 있다. 고속도로통행료수납시스템(TCS: Toll Collection Systrem)은 전국 고속도로를 주행하는 차량의 통행 정보를 실시간으로 제공하므로 교통 상황 예측에 유용하게 활용될 수 있다. TCS 자료는 차량이 입구영업소를 통과한 후 출구영업소를 통과하는 데 소요된 시간으로서, 운전한 시간, 휴게소 체류시간 등을 모두 포함한 통행시간으로 운전자의 운전 특성, 통행 목적, 피로의 정도에 따라 편차가 크게 나타난다. TCS 자료의 통행시간을 기초로 예측된 정보는 이러한 불확실성을 포함하고 있기 때문에 이를 활용하기 다양한 데이터처리 기법이 필요하다. 본 논문에서는 TCS 자료의 효율적인 전처리 및 교통 예측 기법 현황에 대하여 기술하고 향후 발전 방향을 제시하였다.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.209-221
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• 2009

Travel time estimation under given traffic conditions is important for providing drivers with travel time prediction information. But the present expressway travel time estimation process cannot calculate a reliable travel time. The objective of this study is to estimate the path travel time spent in a through lane between origin tollgates and destination tollgates on an expressway as a prerequisite result to offer reliable prediction information. Useful and abundant toll collection system (TCS) data were used. When estimating the path travel time, the path travel time is estimated combining the link travel time obtained through a preprocessing process. In the case of a lack of TCS data, the TCS travel time for previous intervals is referenced using the linear interpolation method after analyzing the increase pattern for the travel time. When the TCS data are absent over a long-term period, the dynamic travel time using the VDS time space diagram is estimated. The travel time estimated by the model proposed can be validated statistically when compared to the travel time obtained from vehicles traveling the path directly. The results show that the proposed model can be utilized for estimating a reliable travel time for a long-distance path in which there are a variaty of travel times from the same departure time, the intervals are large and the change in the representative travel time is irregular for a short period.

• 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.

• Journal of Korean Society of Transportation
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• v.30 no.3
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• pp.71-82
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• 2012

This study analyzed factors affecting daily travel times at each stage of commuters' life cycle. In this study, travel times were dealt with in the context of trip chain. That is, the travel time was defined as the total amount of time commuters had spent to move for daily activities from leaving to coming back home. A commuter's life cycle was divided into 6 stages on a basis of both householder's age and family type: i.e., the unmarried youth period, the family forming period, the children education period, the children youth period, the children independence period, and the aged period. Variables such as commuting times, home-based trip cycle recurrences, and the number of stops differed for each stage of life cycle, the latter of which represents how many places a commuter dropped by during a trip cycle. Several factors were found to affect commuting times at each stage of life cycle as a result of applying a Cox proportional hazard model. The empirical study was conducted using 2010' household travel survey data collected from Gyeonggi-do.