• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.91-103
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• 1999

이 연구는 자동 차량위치 측정기법(Automatic Vehicle Location, AVL)을 이용해서 수집한 교통상황자료를 가지고 구간 통행시간을 산출하는 알고리즘을 개발한다. AVL기법을 이용하는 경우, 처리해야 할 자료량이 많아서 실시간에 정보를 산출하는 것이 힘들다. 따라서 이 연구는 처리해야 할 자료량을 가능한 한 줄이고 자료량이 적은 경우에도 효율적인 구간통행시간을 산출하는 알고리즘을 제시한다. 이 연구의 방법론은 크게 4가지인데, 첫째, 해석 기법, 둘째, 회귀분석, 셋째, 인공지능 및 전문가 시스템, 넷째, 통계분석이다. 이 방법론을 이용해서 세 단계 알고리즘을 개발하는데, 첫째는 실시간 분석통계 알고리즘, 둘째는 과거자료분석 알고리즘, 셋째는 자료응합 알고리즘이다. 이 알고리즘 가운데 자료융합 알고리즘 결과가 산출하고자 하는 구간 통행시간이다. 실시간 분석통계 알고리즘은 연속하는 세 개 구간의 통행 패턴을 이용해서 가운데 구간의 통행시간을 산출하는 방법을 제시한다. 또 실시간 분석통계 알고리즘으로 산출하지 못한 구간은 인접구간 상관도 정보를 이용해서 구간통행시간을 추정한다. 과거자료분석 알고리즘은 회귀분석을 이용해서 시간대별 통행시간 평균과 분산을 구하고, 이 결과를 바탕으로 인접구간 상관도 정보를 오프라인으로 구하는 알고리즘이다. 자료융합 알고리즘은 2가지 단계를 거치는데, 그것은 실시간 자료융합과 최종 자료융합이다. 실시간 자료융합은 실시간에 가까운 자료원의 실시간 분석통계 알고리즘 결과 패턴과 인접구간 상관도 정보를 이용한 구간통행시간 추정 결과를 이용해서 패턴에 따라 다른 방법으로 융합을 하는 알고리즘을 개발한다. 최종 자료융합은 실시간 자료융합 결과와 회귀분석 결과의 패턴을 이용해서 구간 통행시간을 산출한다. 이 연구를 기존 연구와 비교할 때, 세 가지 독차성이 있다. 첫째는 연속하는 세 구간 통행 패턴을 분석하였기 때문에 기존의 노드의존 방식을 탈피하였다는 점이다. 따라서 자료량이 적은 경우도 믿을만한 통행시간을 산출할 수 있다는 것이다. 둘째는 인접구간 상관도 정보를 구간통행시간 산출에 이용하였기 때문에 자료를 효율적으로 이용할 수 있다는 점이다. 셋째는 자료원 패턴을 분류하고 전문가 시스템을 이용하여 자료융합 하였기 때문에 수행속도가 빠르고, 신뢰성있는 정보를 제공한다는 점이다. 이 연구는 개발한 알고리즘 정확도를 검증하기 위해서 두 가지 검증방법을 이용하였다. 첫째는 시뮬레이션을 이용한 것이고, 둘째는 실제 주행조사 분석을 이용한 것이다. 두 가지 검증 결과는 알고리즘 정확도를 보여준다.

• Journal of Korean Society of Transportation
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• v.21 no.5
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• pp.83-95
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• 2003

This study aims to develop travel time estimation and prediction models on the freeway using measurements from vehicle detectors. In this study, we established a travel time estimation model using traffic volume which is a principle factor of traffic flow changes by reviewing existing travel time estimation techniques. As a result of goodness of fit test. in the normal traffic condition over 70km/h, RMSEP(Root Mean Square Error Proportion) from travel speed is lower than the proposed model, but the proposed model produce more reliable travel times than the other one in the congestion. Therefore in cases of congestion the model uses the method of calculating the delay time from excess link volumes from the in- and outflow and the vehicle speeds from detectors in the traffic situation at a speed of over 70km/h. We also conducted short term prediction of Kalman Filtering to forecast traffic condition and more accurate travel times using statistical model The results of evaluation showed that the lag time occurred between predicted travel time and estimated travel time but the RMSEP values of predicted travel time to observations are as 1ow as that of estimation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.1 no.1
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• pp.41-51
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• 2002

As Advanced Traveler Information System(ATIS) is the kernel of the Intelligent Transportation System, it is very important how to manage data from traffic information collectors on a road and have at borough grip of the travel time's change quickly and exactly for doing its part. Link travel time can be obtained by two method. One is measured by area detection systems and the other is estimated by point detection systems. Measured travel time by area detection systems has the limitation for real time information because it Is calculated by the probe which has already passed through the link. Estimated travel time by point detection systems is calculated by the data on the same time of each. section, this is, it use the characteristic of the various cars of each section to estimate travel time. For this reason, it has the difference with real travel time. In this study, Artificial Neural Networks is used for estimating link travel time concerned about the relationship with vehicle detector data and link travel time. The method of estimating link travel time are classified according to the kind of input data and the Absolute value of error between the estimated and the real are distributed within 5$\~$15minute over 90 percent with the result of testing the method using the vehicle detector data and AVI data of Namsan Tunnel $\#$1. It also reduces Time lag of the information offered time and draws late delay generation and dissolution.

• Journal of Korean Society of Transportation
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• v.28 no.4
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• pp.107-118
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• 2010

Wireless communication technologies including vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) enable the development of more sophisticated and effective traffic information systems. This study presents a method to estimate vehicular travel times in a vehicular ad hoc network (VANET) environment. A novel feature of the proposed method is estimating individual vehicle travel times through advanced on-board units in each vehicle, referred to as self-estimated travel time in this study. The method uses travel information including vehicle position and speed at each given time step transmitted through the V2V and V2I communications. Vehicle trajectory data obtained from the VISSIM simulator is used for evaluating the accuracy of estimated travel times. Relevant technical issues for successful field implementation are also discussed.

• 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.19 no.6
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• pp.171-182
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• 2001

Travel Time is an important characteristic of traffic conditions in a road network. Currently, there are so many road users to get a unsatisfactory traffic information that is provided by existing collection systems such as, Detector, Probe car, CCTV and Anecdotal Report. This paper presents the results achieved with Data Fusion Model, Hybrid Neuro Fuzzy System for on - line estimation of travel times using RTMS(Remote Traffic Microwave Sensor) and Probe Data in the signalized arterial road. Data Fusion is the most important process to compose the various of data which can present real value for traffic situation and is also the one of the major process part in the TIC(Traffic Information Center) for analyzing and processing data. On-line travel time estimation methods(FALEM) on the basis of detector data has been evaluated by real value under KangNam Test Area.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.12
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• pp.1373-1380
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• 2014

In order to calculate accurate traffic and traffic speed, qualified and sufficient GPS data should be provided. However, it is difficult to provide accurate traffic information using restricted GPS data from probe vehicles because of communication costs. This paper developed a algorithm that recovers links omitted by restricted GPS data with topology information, and calculate traffic speed with original links and recovered links. T traffic information service of city with a new algorithm can provide more accurate traffic and traffic speed than the original system.

• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.157-168
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• 2006

Spatial detection system such as AVI, GPS, and Beacon etc. can provide spatial travel time only after a vehicle Passes through a road section. In this context, majority of the existing studies on the link travel time estimation area has focused on the arrival time-based link travel time estimation. rather than departure time-based link travel time estimation. Even if some of the researches on this area have developed departure time-based link travel time estimation algorithms, they are limited in that they are not applicable in a real-time mode. The objective of this study is to develop an departure time-based link travel time estimation algorithm which is applicable in a real-tine mode. Firstly, this study discussed the tradeoff between accuracy and timeliness of the departure time-based on-line link travel time estimates. Secondly, this study developed an departure time-based on-line link travel time estimation algorithm which utilizes the Baysian inference logic. It was found that the proposed approach could estimate departure time-based link travel times in a real-time context with an acceptable accuracy and timeliness.

• Journal of Korean Society of Transportation
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• v.2 no.1
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• pp.103-119
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• 1984

복잡다기해지는 도시교통문제를 효율적으로 대처하려면 제도시교통정책에 의한 교 통분담율효과를 사전에 추정할 수 있어야 한다. 단기간의 교통분담율효과를 추정하는데 미 국 및 구라파 등지에서 널리 이용되고 있는 모형이 개별교통모형(Disaggregate Travel Demand Model)이다. 본 연구의 목적은 로짓모형(Multinomial Logit Model)을 서울시의 종 로축을 이용하는 출근통행자를 대상으로 실시한 조사결과에 적용하여 매개함수(Parameters) 를 추정함에 있다. 조사는 1980년7월5일부터 7월15일까지 10일간 종로축을 이용하는 통행자 536명에게 실시되었다. 조사실시전 서울시의 교통체계의 특성과 통행자의 행태를 면밀히 분 석하여 적합한 변수를 선정하였다. 여러 가지로 변수와 표본의 변형을 시도한 결과 교통비 용을 소득으로 나눈 변수와 시기시간(OVTT)을 거리로 나눈 변수를 포함한 모형이 가장 논 리적인 것으로 나타났다. 한편 표본은 고소득층과 저소득층으로 구분하여 추정한 모형이 비 교적 만족스러운 결과를 나타내었다. 이는 우리나라 대도시의 경우 소득계층에 따라 교통수 단선택범위가 한정되기 때문이다. 마지막으로 고소득층과 저소득층의 시간가치를 각각 산정 하였는바, 이는 교통시간의 매개변수와 교통비용의 매개변수를 나눔으로서 구해질 수 있다. 시간가치는 고소득층은 910원 저소득층은 582원으로 각각 산출되었다.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.147-155
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• 2005

The purpose of this paper is to develop a method for estimation of reliable path-travel time using data obtained from the toll collection system on freeways. The toll collection system records departure and arrival time stamps as well as the identification numbers of arrival and destination tollgates for all the individual vehicles traveling between tollgates on freeways. Two major issues reduce accuracy when estimating path-travel time between an origin and destination tollgate using transaction data collected by the toll collection system. First, travel time calculated by subtracting departure time from arrival time does not explain path-travel time from origin tollgate to destination tollgate when a variety of available paths exist between tollgates. Second, travel time may include extra time spent in service and/or rest areas. Moreover. ramp driving time is included because tollgates are installed before on-ramps and after off-ramps. This paper describes an algorithm that searches for arrival time when departure time is given between tollgates by a Progressive Iterative Forward and Backward (PIFAB) search method. The algorithm eventually produces actual path-travel times that exclude any time spent in service and/or rest areas as well as ramp driving time based on a link-based procedure.