• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.51-61
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• 2002

In this dissertation, We demonstrated the Travel Time forecasting model in the freeway of multi-section with regard of drives' attitude. Recently, the forecasted travel time that is furnished based on expected travel time data and advanced experiment isn't being able to reflect the time-lag phenomenon specially in case of long distance trip, so drivers don't believe any more forecasted travel time. And that's why the effects of ATIS(Advanced Traveler Information System) are reduced. Therefore, in this dissertation to forecast the travel time of the freeway of multi-section reflecting the time-lag phenomenon & the delay of tollgate, we used traffic volume data & TCS data that are collected by Korea Highway Cooperation. Also keep the data of mixed unusual to applicate real system. The applied model for forecasting is consisted of feed-forward structure which has three input units & two output units and the back-propagation is utilized as studying method. Furthermore, the optimal alternative was chosen through the twelve alternative ideas which is composed of the unit number of hidden-layer & repeating number which affect studying speed & forecasting capability. In order to compare the forecasting capability of developed ANN model. the algorithm which are currently used as an information source for freeway travel time. During the comparison with reference model, MSE, MARE, MAE & T-test were executed, as the result, the model which utilized the artificial neural network performed more superior forecasting capability among the comparison index. Moreover, the calculated through the particularity of data structure which was used in this experiment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.631-638
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• 2023

This paper is to introduce methodologies of travel time reliability evaluation using daily traffic volumes. The methodologies include desirable speed concept, the relation between averaged daily speeds and daily traffic volumes, the standardized way in integration of travel time deviations obtained from continuous highway sections. The study began with traffic data collection from a freeway line with long lasting congestion. And then, provided establishment of the relation between averaged daily speeds and daily traffic volumes, and usability of Point estimate method (PEM) to integrate travel time deviations of sections. Based on the relation between averaged daily speeds and daily traffic volumes, it is identified that travel time reliability begins to decrease around LOS (Level of Service) C even before LOS D or F. It may be concluded that travel time reliability could be evaluated based on daily traffic volumes in highway sections using standardized PEM. The methodologies introduced in the paper, could be useful in practicing evaluation of travel time reliability during the works of highway operation or highway planning.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1873-1879
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• 2014

There are various methodologies to forecast the travel time using real-time data but the K-nearest neighborhood (KNN) method in general is regarded as the most one in forecasting when there are enough historical data. The objective of this study is to evaluate applicability of KNN method. In this study, real-time and historical data of toll collection system (TCS) traffic flow and the dedicated short range communication (DSRC) link travel time, and the historical path travel time data are used as input data for KNN approach. The proposed method investigates the path travel time which is the nearest to TCS traffic flow and DSRC link travel time from real-time and historical data, then it calculates the predicted path travel time using weight average method. The results show that accuracy increased when weighted value of DSRC link travel time increases. Moreover the trend of forecasted and real travel times are similar. In addition, the error in forecasted travel time could be further reduced when more historical data could be available in the future database.

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.145-154
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• 2008

The purpose of this study is to evaluate the quality of on-line departure time-based link travel time estimates. For this, accuracy (i.e. estimation error) and timeliness (i.e. degree of time lag) are proposed as MOE of the quality of on-line link travel time estimates. Then the relationship between quality of link travel time estimates and link length and level of congestion is analyzed. It was found that there is trade-off between the accuracy and timeliness of link travel time estimates. The estimation error was modeled to consist of two components: one is systematic error and the other is mean square error which reflects level of congestion. further, time lag was again segmented into three parts for the analysis purpose. There are minimum one, congestion-related one, and update interval-related one. From the real-world data using AVI system, it was revealed that regardless of the link length and level of congestion, 10 minutes of time lag occurs in general.

• Journal of Korean Society of Transportation
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• v.18 no.2
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• pp.7-16
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• 2000

This study Presents an guideline of the exclusive bus and/or truck lane on 8 lanes freeways using FREFLO model and INTEGRATiON model. Four alternatives : do nothing, bus exclusive lane, truck exclusive lane, bus and truck exclusive lane, were evaluated using average daily vehicle travel time as measures of effectiveness. It is found that bus and truck exclusive lane is the most effective alternative reducing total travel time by 7% when ADT is below 80,000 vehicle/day. However, when ADT is above 80,000 vehicle/day and bus Proportion is above 12%, bus exclusive lane is the most effective alternative reducing total travel time by more than 5.6%. It is further found that INTEGRATION, the stochastic and microscopic model, is more sensitive than FREFLO, the deterministic and macroscopic model, in evaluating the effectiveness of four alternatives.

• 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.34 no.4
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• pp.341-353
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• 2016

Highway is mainly in charge of middle-long distance of vehicular travel. Trip length has shown a growing trend due to increased commute distances by the relocation of public agencies. For this reason, the proportion of driver-driven accidents, caused by their fatigue or sleepiness, are very high on highways. However, existing studies related to accident prediction have mainly considered external factors, such as road conditions, environmental factors and vehicle factors, without driving behavior. In this study, we suggested an accident index (FDR, Fatigued Driving Rate) based on traffic behavior using large-scale Car Navigation path data, and exlpored the relationship between FDR and traffic accidents. As a result, FDR and traffic accidents showed a high correlation. This confirmed the need for a paradigm shift (from facilities to travel behavior) in traffic accident prediction studies. FDR proposed in this study will be utilized in a variety of fields. For example, in providing information to prevent traffic accidents (sleepiness, reckless driving, etc) in advance, utilization of core technologies in highway safety diagnostics, selection of priority location of rest areas and shelter, and selection of attraction methods (rumble strips, grooving) for attention for fatigued sections.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.179-190
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• 2009

Travel time is one of the most important traffic parameters to evaluate operational performance of freeways. A variety of methods have been proposed to estimate travel times. One feasible solution to estimating travel times is to utilize existing loop detector-based infrastructure since the loops are the most widely deployed detection system in the world. This study proposed a new approach to estimate travel times for freeways. Inductive vehicle signatures extracted from the loop detectors were used to match vehicles from upstream and downstream stations. Ground-truthing was also conducted to systematically evaluate the performance of the proposed algorithm by recognizing individual vehicles captured by video cameras placed at upstream and downstream detection stations. A lexicographic optimization method vehicle reidentification algorithm was developed. Vehicle features representing the characteristics of individual vehicles such as vehicle length and interpolations extracted from the signature were used as inputs of the algorithm. Parameters associated with the signature matching algorithm were calibrated in terms of maximizing correct matching rates. It is expected that the algorithm would be a useful method to estimate freeway link travel times.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.05a
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• pp.113-118
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• 2001

교통혼잡의 묘사를 보다 구체적으로 하기 위한 Mesoscopic시뮬레이션 모형으로서 INTEGRATION을 소개한다. 모형의 기본구조가 설명되고, 특히 응용사례로서 경부고속도로 축을 중심으로 한 주거지역의 급속한 팽창으로 야기된 고속도로상의 교통대안을 평가하려는데 초점을 맞추고 있다. 교통대안은 혼잡을 완화시키는데 타당하고 기술적으로도 실현가능한 대안이 제시된다. 이러한 대안들은 거시 및 미시 모의실험모형을 통해 면밀히 분석 평가되며 또한 대안을 도출하고 평가하는 과정의 제시로서 교통량조사에 근거한 OD 도출, Subarea 네트워크 분석 및 통합된 네트워크 모의실험과 같은 새로운 기법들이 아울러 제시된다. 대안의 대부분은 네트워크 개선에 관련한 것이다. 반포 IC 진출입로 공사(Al), 위빙 제거를 기초로 한 서초 IC TSM(A2), 서초-양재 구간의 고속 저속 분리(A3), 헌릉 IC(A4)의 신설, 판교 JC 개선(A5), 백현 IC(A6)신설. 가장 자본 집약적인 대안은 A4, A6순이다. A1, A5, A6은 구간은 짧으나, 자본 집약적이며 어느 정도의 공사 기간이 소요된다. 가장 비용이 적게 소요되는 대안은 A2, A3이다. A2는 시행이 용이하나, A3의 경우 공사기간 중 교통분산 대책이 필요하다. A1, A6은 속도증가와 통행시간 절감의 측면에서 가장 비용대비 효율적인 것으로 분석되었다. 시뮬레이션의 한계 및 개선방안이 함께 검토되었다.