• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.107-116
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• 2004

VMS를 통한 정보제공에는 과도반응과 통행집중의 위험부담이 따른다. 즉 대안경로간에 이루어져야 할 통행배분을 정확히 유도할 수 있는 VMS 메시지란 존재치 않는다. VMS 메시지에 의해 특정 경로가 교통상황이 타 경로에 비해 좋다고 정보가 주어질 때, 그 정보에 대한 과도반응과 그 특정경로에 대한 통행집중 문제가 발생하여 정보제공에 의해 오히려 상황이 악화될 수 있다. 본 연구에서는 대안경로간의 물리적 특성 측면에서 우열이 있는 가상 네트워크를 대상으로 하여, 과도반응과 통행집중 문제를 극복하고 대안경로간의 적절한 통행배분을 달성하기 위한 VMS 운영알고리즘을 개발하는 것을 목표로 한다. VMS정보제공 결과, 즉 VMS를 통해 상황이 좋다고 알려준 경로에 통행이 집중할 경우 문제가 될 것인가 여부를 미리 예측해 보고, 문제가 될 경우 정보제공 전략을 수정하도록 하는, 피드백 제어에 예측적 방식을 접목하였다. 본 연구에서 제안한 알고리즘의 주요 기능은 다음과 같다. 1. 교통량, 속도 등에 대한 실시간 모니터링 시스템이 구축되어 있음을 전제로 한다. 2. 실시간 제어에는 모니터링 결과와 이에 근거한 정보제공전략의 시행사이에는 시간차가 존재한다. 이러한 시간차이로 인하여 단기예측이 필요하고, 이를 수행하는 모듈이 있다. 3. 정보제공 결과로 특정 경로에 과부하가 걸리는지 여부를 예측하기 위하여, 그 판단기준으로 그 경로의 실제 용량 산정이 필요하다. 이에 혼잡의 시공간적 전개에 따라 변하는 동적 용량을 산정하는 모듈이 있다. 4. 대안 경로간 통행배분 목표치를 수리적으로 산정할 수는 있으나, 이를 자동적으로 이루어 주는 메시지는 존재하지 않는다. 아울러 현실적으로 예측 불가능한 외란을 모형에 의존하여 예측하기 보다는, 계속적인 피드백 레귤레이터(Regulator) 작동에 의해 보정하여 목표를 달성해 가는 자동제어 기능을 갖고 있다.

• Proceedings of the KOR-KST Conference
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• 1995.12a
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• pp.111-124
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• 1995

첨단 교통 체계(Intelligent Transport Systems)의 중요한 요소인 첨단 교통 관리 체계(Advanced Traffic Management Systems)의 성공 여부는 교통정보를 어떻게 제공하고 통제하는데 의존하다. 즉, 정보 제공 방식과 이데 대한 운전자의 반응을 정확하게 파악하고 예측하여야 ITS를 성공적으로 구축할 수 있다. 이 논문에서는 동적 차량 길잡이 장치의 효용성을 평가하기 위한 확률적 통행배정모형을 개발하는 것이다. 개발된 통행배정모형은 운전자의 동적행태조정(Dynamic Behavioural Adjustment)을 명백하게 확솔 과정(Stochastic Process)으로 표현하여 기존의 모형에 비해 통해자들의 행태를 더욱 실제적으로 반영한다. 특히, 각 통행자들에게 K개의 최소경로시간을 제공해줌으로 인하여 통행자의 노선선택에 대한 선택폭을 증가시켜준다. 통행경로의 선택폭의 증가는 쟁점으로 대두되는 문제(교통항제소에서는 차량 길잡이 보유 운전자에게 체계최적(System Optimum)와 이용자최적(User Equilibrium)중 어떠한 원칙하에 교통정보를 제공하여야 하는가에 대한 해결 방안이다. 왜냐하면 만약 교통급제소에서 운전자에게 통행정보를 체계 최상을 하기 위해 정보를 제공하고자 하면, 길잡이 장착 운전자는 더 이상 제공된 정보를 따르지 않고 자기 스스로의 경에 의해 이용자 최상을 달성하고자 할 것이다. 이 논문의 목적은 이러한 복잡한 통행자의 경로선택행위를 반영하는 확률적 평형 통행 배정 모형을 여러가지 통계기법을 도입하여 개발하는 것이다.

• 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.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.109-120
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• 2004

Since the late of 1990, there have been number of studies on the required number of probe vehicles and/or optimal aggregation interval sizes for travel time estimation and forecasting. However, in general one to five minutes are used as aggregation intervals for the travel time estimation intervals for the travel time estimation and/or forecasting of loop detector system without a reasonable validation. The objective of this study is to deveop models for identifying optimal aggregation interval sizes of loop detector data for travel time estimation and prediction. This study developed Cross Valiated Mean Square Error (CVMSE) model for the link and route travel time forecasting, The developed models were applied to the loop detector data of Kyeongbu expressway. It was found that the optimal aggregation sizes for the travel time estimation and forecasting are three to five minutes and ten to twenty minutes, respectively.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.89-100
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• 2008

In an urban network controlled by traffic signals, there is an interaction between the signal timing and the routes chosen by individual road users. This study develops a bi level programming model for traffic signal optimization in networks with path based traffic assignment. In the bi level programming model, genetic algorithm approach has been proposed to solve upper level problem for a signalized road network. Path based traffic assignment using column generation technique which is proposed by M.H. Xu, is applied at the lower-level. Genetic Algorithm provieds a feasible set of signal timings within specified lower and upper bounds signal timing variables and feeds into lower level problem. The performance of this model is investigated in numerical experiment in a sample network. In result, optimal signal settings and user equilibrium flows are made.

• 한국ITS학회:학술대회논문집
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• 2004.11a
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• pp.154-162
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• 2004

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.145-153
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• 2008

Existing shortest-path algorithms mainly consider a single attribute. But traveler actually chooses a route considering not single attribute but various attributes which are synthesized travel time, route length, personal preference, etc. Therefore, to search the optimal path, these attributes are considered synthetically. In this study route searching algorithm which selects the maximum utility route using discrete choice model has developed in order to consider various attributes. Six elements which affect route choice are chosen for the route choice model and parameters of the models are estimated using survey data. A multinomial logit models are developed to design the function of route choice model. As a result, the model which has route length, delay time, the number of turning as parameter is selected based on the significance test. We use existing shortest path algorithm, which can reflect urban transportation network such as u-turn or p-turn, and apply it to the real network.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.599-604
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• 2010

In this study, the value of travel time was estimated with reflecting the fuel cost according to travel distance. The main objective of this study is whether the addition of the fuel cost as a factor for route choice behavior is appropriate or not, through the stated preference survey. The route choice model was developed using SP survey technique with the consideration of level difference and the value of travel time, toll and fuel costs. Consequently, the fuel cost is identified as a main factor like travel time and toll cost in choosing routes from drivers' viewpoints. Nevertheless, since toll costs are recognized as out-of-pocket expenses whereas fuel costs as periodical expenses, it seems drivers are more sensitive to toll than fuel costs.

• Journal of the Korean Society for Railway
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• v.14 no.3
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• pp.276-284
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• 2011

In our study, we present a new LOGIT-based traffic assignment model applicable to intercity railway network. Most traffic assignment models have been developed for public transit assignment in urban area, so that they are known to produce unrealistic results in intercity railway demand analysis. Especially, since the introduction of KTX, more passengers are using a route including KTX service and the schedule becomes more compatible with transfer. Our study presents a new LOGIT-based traffic assignment model considering passenger transfer. To do so, we suggest a new route search algorithm to find K paths with non increasing order in the utility value.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.5
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• pp.988-995
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• 2009

One of the most popular services of Telematics is a shortest path finding from a starting point to a destination. In this paper, a dynamic shortest path finding system with forecasting result of traffic flow in the future was developed and various experiments to verify the performance of our system using real-time traffic information has been conducted. Traffic forecasting has been done by a prediction system using Bayesian network. It searched a dynamic shortest path, a static shortest path and an accumulated shortest path for the same starting point and destination and calculated their travel time to compare with one of its real shortest path. From the experiment, over 75%, the travel time of dynamic shortest paths is the closest to one of their real shortest paths than one of static shortest paths and accumulated shortest paths. Therefore, it is proved that finding a dynamic shortest path by applying traffic flows in the future for intermediated intersections can give more accurate traffic information and improve the quality of services of Telematics than finding a static shortest path applying by traffic flows of the starting time for intermediated intersections.