• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.1105-1113
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• 2013

Understanding the characteristics of truck-involved crashes is of keen interest because such crashes are highly associated with greater potential leading to severer injury. The purpose of this study is to identify factors affecting injury severity of truck-involved crashes on freeways. In addition, a binary logistic regression technique is applied to identify causal factors affecting truck crash severity under normal and adverse weather conditions. Major findings from the analyses are discussed with truck operations strategies including speed enforcement, variable speed limit, and truck lane restriction, from the safety enhancement point of view. The results of this study would be useful for developing traffic control and operations strategies to reduce truck-involved crashes and injury severity in practice.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.111-121
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• 2008

Using variable speed limits (VSL) is a key strategy for preventing traffic accidents and alleviating traffic congestion. This study proposes an algorithm to operate VSLs on freeways for traffic safety. The proposed algorithm consists of two components based on accident likelihood estimation and analysis of safe stopping distance under various environmental conditions. A binary logistic regression technique is used for estimating accident likelihood. It is expected that the proposed algorithm would be successfully applied in practice in support of an integrated traffic and environmental condition monitoring system. Technical issues associated with the field implementation are also discussed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.47-54
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• 2021

The number of freeway traffic accidents in Korea is about 4,000 as of 2020, and deaths per traffic accident is about 3.7 times higher than other roads due to non-recurring congestion and high driving speed. Most of the accident types on freeways are side and rear-end collisions, and one of the main factors is hazard traffic flow caused by merge, diverge and accidents. Therefore, the hazard traffic flow, which appears in a continuous flow such as a freeway, can be said to be important information for the driver to prevent accidents. This study tried to classify hazard traffic flows, such as the speed change point and the section where the speed difference by lane, using individual vehicle information. The homogeneous segment of speed was classified using spatial separation based on geohash and space mean speed that can indicate the speed difference of individual vehicles within the same section and the speed deviation between vehicles. As a result, I could extract the diverging influence segment and the hazard traffic flow segment that can provide dangerous segments information of freeways.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.581-586
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• 2006

Incidents, which is unexpected unusual events such as traffic accidents, have increased on the most roads in Korea. The obstruction of a fluent traffic flow occurred by incidents causes the traffic congestion and decreases the capacity. The Wavelet technique was applied to detect the road section and the happening time of incidents on urban freeways in this study, and this technique has been widely used in many engineering fields such as an electrical engineering, etc. The availability and validity of the Wavelet technique to the detection of incidents was examined by the occupancy rate, the important element of traffic flows, which is extracted from the data of detectors installed on Seoul Urban freeways. Then, this result is compared to the California Algorithm and the Low-Pass Filtering Algorithm among basic present detection algorithms, which are based on the occupancy rate. As a result, the false alarm rate of this method was similar as that of the California algorithm and the Low-Pass Filtering algorithm, but the detection rate is higher.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.101-116
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• 2012

Accident prediction models have been utilized to predict accident possibilities in existing or projected freeways and to evaluate programs or policies for improving safety. In this study, a traffic accident prediction model for freeways was developed for the above purposes. When selecting variables for the model, the highest priority was on the ease of both collecting data and applying them into the model. The dependent variable was set as the number of total accidents and the number of accidents including casualties in the unit of IC(or JCT). As a result, two models were developed; the overall accident model and the casualty-related accident model. The error structure adjusted to each model was the negative binomial distribution and the Poisson distribution, respectively. Among the two models, a more appropriate model was selected by statistical estimation. Major nine national freeways were selected and five-year dada of 2003~2007 were utilized. Explanatory variables should take on either a predictable value such as traffic volumes or a fixed value with respect to geometric conditions. As a result of the Maximum Likelihood estimation, significant variables of the overall accident model were found to be the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volume to the number of curved segments between ICs(or JCTs). For the casualty-related accident model, the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volumes had a significant impact on the accident. The likelihood ratio test was conducted to verify the spatial and temporal transferability for estimated parameters of each model. It was found that the overall accident model could be transferred only to the road with four or more than six lanes. On the other hand, the casualty-related accident model was transferrable to every road and every time period. In conclusion, the model developed in this study was able to be extended to various applications to establish future plans and evaluate policies.

• Journal of Korean Society of Transportation
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• v.16 no.1
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• pp.165-186
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• 1998

선진 외국의 대도시에서는 도시고속도로의 원할한 교통류 흐름을 유지하기 위하여 다양한 교통류 관리기법을 도입.시행하고 있으며, 운영전략의 개발과 교통류 관리기법의 평가를 위한 다양한 모델을 개발.적용하고 있다. 서울시 도시고속도로의 경우에는 외국 도시고속도로의 교통류와 상이한 특성이 많아 기존에 개발된 모델의 적용이 매우 어려운 실정이며, 현재가지 실제교통류 관리를 위한 목적으로 개발되어 적용되는 모델은 없는 실정이다. 따라서 향후 서울시 도시고속도로 교통관리시스템의 효율적인 운영을 위하여 교통류 관리기법을 선정하고, 각 기법별로 교통류 소통상황을 예측할 수 있는 기능을 갖춘 국내 실정에 맞는 도시고속도로 교통류 예측 모델의 개발이 반드시 필요하다. 본 연구의 목적은 도시고속도로를 대상을 교통류의 현상을 잘 표현하며, 도시고속도로 교통류 관리를 위한 기법의 개발 및 평가가 가능한 시뮬레이션 모델(KUFRE:Korean Urban Freeway Simulation Model)을 개발하는 것이 목적이다.

• Journal of Korean Society of Transportation
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• v.12 no.1
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• pp.151-172
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• 1994

The objective of study is to evaluate design standards related to the allowable truck speeds, taper length and sign requirements together with the operating practices and economic justification for climbing lanes. Field surveys were carried out on seven climbing lanes, three on two-lane and four on four-lane freeways. Data collected are traffic volume, speed, usage rate and delay. It is found that current design criteria for determining the length of climbing lane, taper lengths, and traffic sign requirements must be upgraded. It is also recommended that regulations on the use of climbing lane be established to make it more effective. Further, economic analysis revealed that the climbing lane is economically justified for two-lane and four-lane freeway if the AADT is over 4,577 and 5,116 vehicles respectively.

• Journal of Korean Society of Transportation
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• v.14 no.3
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• pp.7-26
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• 1996

The estimation of real-time Origin-Destination(O-D) parameters, which gives travel demand between combinations of origin and destination points on a urban freeway network, from on-line surveillance traffic data is essential in developing an efficient ATMS strategy. On this need a real-time O-D parameter estimation model is formulated as a parameter adaptive filtering model based on the extended Kalman Filter. A Monte Carlo test have shown that the estimation of time-varying O-D parameter is possible using only traffic counts. Tests with field data produced the interesting finding that off-ramp volume predictions generated using a constant freeway O-D matrix was replaced by real-time estimates generated using the parameter adaptive filter.

• Journal of Korean Society of Transportation
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• v.25 no.2 s.95
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• pp.109-120
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• 2007

This study developed a methodology that can reflect more realistic traffic flow to understand platoons on highways. The understanding of the phenomenon nay secure highway safety and authoritative credibility in highway planning. In this study platoons generated by 'random effects' of cars are modeled, and this model is validated using a real data set acquired from the Jayu Expressway in Kyonggi Province, Korea.

• Journal of Navigation and Port Research
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• v.36 no.7
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• pp.591-597
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• 2012

Generally an urban freeway means a primary arterial which provides road users with a free-flow speed, except for ramp junctions during rush hours. However, most road users suffer from traffic congestion in the basic segments as well as in the ramp junctions of urban freeway during rush hours, because most road users prefer urban freeways to local roads in the urban areas. This study then intends to analyze lane traffic characteristics of urban freeway basic segments having more freight vehicles during rush hours, find the lane showing a high correlation with the segment speed between lane speeds, and finally suggest a segment-speed predictive model by the lane speed of urban freeway basic segments during rush hours.