• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.81-89
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• 2015

Crashes that occur at tollgates have different characteristics compared to those of the mainline on expressways in terms of crash cause, crash type, and vehicle type. Due to this fact, the safety performance function (SPF) focused on the expressway tollgates, apart from the mainline, should be developed. The aim of this study is, therefore, to identify the influential factors and develope a SPF for crashes at tollgates. Firstly, we established independent variables affecting crashes at tollgates through literature review and descriptive statistical analysis. Based on these variables, two negative binomial regression models with different form of independent variables were developed and goodness-of-fits of each model were compared. According to the results, the number of crashes increases i) as AADT, Hi-pass rate, and heavy vehicle rate increase, ii) as average lane width decreases, iii) on the mainline tollgate type. The safety performance function developed in this study could be applied to select hot-spots for expressway tollgates.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.34-48
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• 2019

The purpose of this study was two-fold; first, to develop safety performance functions (SPF) using transportation-related big data for all types of roads in Korea were developed, Second, to provide basic information to develop measures for relatively dangerous roads by evaluating the safety grade for various roads based on it. The coordinates of traffic accident data are used to match roads across the country based on the national standard node and link system. As independent variables, this study effort uses link length, the number of traffic volume data from ViewT established by the Korea Transport Research Institute, and the number of dangerous driving behaviors based on the digital tachograph system installed on commercial vehicles. Based on the methodology and result of analysis used in this study, it is expected that the transportation safety improvement projects can be properly selected, and the effects can be clearly monitored and quantified.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 1997.11a
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• pp.91-100
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• 1997

암호학적으로 안전한 해쉬 함수는 디지털 서명, 메시지 인증, 키 유도와 같은 분야에서 중요한 암호 도구이다 현재까지 제안된 소프트웨어로 고속 수행이 가능한 해쉬 함수들의 대부분은 Rivest가 제안한 MD4의 설계 원리에 기반을 두고 있다. 이들 MD 계열 해쉬 함수 중에서 현재 안전하다고 알려진 전용 해쉬 함수는 SHA-1, RIPEMD-160, HAVAL 등이다. 본 논문에서는 이들 세 가지 해쉬 함수들의 장점에 기반하여 이들 함수들이 가지는 안전성을 최대한 유지하면서 보다 효율적인 새로운 해쉬 함수를 제안한다. 제안된 해쉬 함수는 임의 길이 메시지를 512비트 단위로 처리하여 160비트의 출력을 가지며, 입력 데이터에 의존한 순환이동(data-dependent rotation)의 특징을 가짐으로써 기존에 알려진 공격에 강인함을 보장한다. 또한 제안된 해쉬 함수를 이용한 메시지 인증 코드(Message Authentication Code:MAC) 구성 알고리즘을 제안한다 MAC은 두 번째 입력, 즉 비밀키를 가진 해쉬 함수로 keyed 해쉬 함수라고 하며, 메시지 출처 인증과 무결성 확인을 제공한다. 제안된 MAC은 최대 160-비트의 키를 사용하며 해쉬 결과보다 같거나 적은 MAC 결과를 가지며, 성능 면에서 사용되는 해쉬 함수에 비해 약 10% 정도의 저하를 초래한다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.7 no.4
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• pp.59-71
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• 1997

암호적으로 안전한 해쉬 함수는 디지털 서명, 메세지 인증, 키 유도와 같은 분야에서 중요한 암호도구이다. 현재까지 제안된 소프트웨어로 고속 수행이 가능한 해쉬 함수들의 대부분은 Rivest가 제안한 MD4의 설계 원리에 기반을 두고 있다. 이들 DM계열 해쉬 함수 중에서 현재 안전하다고 알려진 전용 해쉬 함수는 SHA-1, RIPEMD-160, HAVAL등이다.본 논문에서는 디들 세가지 해쉬 함수들의 장점에 기반하여 이들 함수들이 가지는 안전성을 최대한 유지하면서 보다 효율적인 새로운 해쉬 함수를 제안한다. 제안된 해쉬 함수는 임의 길이 메시지를 512비트 단위로 처리하여 160비트의 출력을 가진다. 제안된 해쉬 함수는 입력 데이터에 의존한 순환이동(data-dependent rotation)의 특징을 가짐으로써 기존에 알려진 공격에 강인함을 보장하며 두 새의 충돌 메시지 발견을 위해서는 생일공격에 의해 2연산이 요구되어진다고 추측된다. 제안된 해쉬 함수의 성능은 수행 속도면에서 RIPEMD-160보다 약 30%보다는 약 7%효율적이다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.397-405
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• 2015

In the past, expressways focused on mobility. However, the paradigm of expressways fuction today has been changed from fast expressways to safe expressways as people's quality of living and consciousness level heightened. In 2012, 3,550 traffic accidents occurred on expressways and 371 people died. The fatality rate of traffic accidents on expressways is almost twice that on general national roads. This study developed accident forecast models (safety performance functions) based on the number of traffic accidents and traffic volumes on six major lines on expressways. It is difficult to forecast safety performance functions for each expressway line because the lines and the scales of expressways are different from each other; therefore, integrated safety performance functions of six lines were determined first, and the coefficients, which can correct the traffic accidents on each line, were calculated. It is believed that this study will contribute in the safer management of expressways by being used as basic information in the establishment of traffic safety strategies for each expressway line in prevention of traffic accidents. Moreover, more studies would be required in the future, which would suggest reliable accident forecasts by calculating correction coefficients by line through integrated models by groups dependent on the characteristics of each line.

• ICROS
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• v.22 no.2
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• pp.29-33
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• 2016

본 기술 특집호에서는 최근메 강인제어 분야에서 많이 주목받고 있는 사전규정 오차 구속제어기법들메 대해 기본적인 개념과 각 구속제어 기법들이 특징들을 소개한다. 기존의 제어기법들은 안정도 및 일정한 출력성능은 보장하지만 선정된 제어기 게인 값에 따라 추종성능이 민감하게 변하며 안전을 위한 제약이 없는데 반해 이러한 구속제어는 최소한의 게인 선정으로 오버슈트, 정상오차 등에 대해 사전에 규정한 성능범위를 만족하도록 강제로 구속시켜 출력성능 및 안전성이 동시에 보장되도록 한다. 이러한 구속제어는 오버슈트에 크게 영향을 받는 정밀기기 위치제어, 힘 제어에서 안전성을 확보해주며 외란이나 시스템 불확실성에 매우 강인한 특성을 갖는다. 가장 먼저 연구된 구속제어는 funnel 제어로서 시스템의 동적 모델을 포함하지 않는 비모델 기준 제어기법이다. 추종오차의 초기값이 오차에 대한 사전 구속함수로 구성된 funnel (깔데기) 안에 있으면 항상 사전메 규정된 오차범위 내에 머물도록 funnel 제어기가 작동하며 PD 제어와 구조가 유사하다. 다음으로 tanh 함수와 추종오차 변환을 결합한 방법으로서 전통적인 순환적 (recursive) 제어방법인 backstepping 제어와 결합하는 방법이다. 최종적므로 좀더 단순한 오차변환을 통해 오차에 대한 switching을 이용한 기법은 제어기 구조를 단순하게 만들고 기존의 제어기와 편리하게 결합할 수 있다. 이러한 구속제어 기법들은 또한 미지의 시스템에 특성에 대해 관측기나 지능제어를 이용한 근사함수를 요구하지 않는다. 본 특집호에서는 최근까지 연구된 구속제어에 대한 간단한 이론과 적용 결과들을 제시하기로 한다.

• Journal of Korean Society of Transportation
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• v.31 no.4
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• pp.85-94
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• 2013

The Continuous Risk Profile (CRP) has been well known to be the most accurate and efficient among existing network screening methods. However, the classical CRP uses safety performance functions (SPFs) which require a huge investment to construct a database system. This study aims to suggest a new CRP method using average crash frequencies of homogeneous groups, instead of SPFs, as rescaling factors. Hierarchical clustering analysis is performed to classify freeway segments into homogeneous groups based on the data of AADT and number of lanes. Using the data from I-880 in California, the proposed method is compared to other several network screening methods. The results show that the proposed method decrease false positive rates while it does not produce any false negatives. The method developed in this study can be easily applied to screen freeway networks without any additional complex database systems, and contribute to the improvement of freeway safety management systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.203-213
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• 2021

A vehicle crash occurs due to various factors such as the geometry of the road section, traffic, and driver characteristics. A safety performance function has been used in many studies to estimate the relationship between vehicle crash and road factors statistically. And depends on the purpose of the analysis, various characteristic variables have been used. And various characteristic variables have been used in the studies depending on the purpose of analysis. The existing domestic studies generally reflect the average characteristics of the sections by quantifying the traffic volume in macro aggregate units such as the ADT, but this has a limitation that it cannot reflect the real-time changing traffic characteristics. Therefore, the need for research on effective aggregation units that can flexibly reflect the characteristics of the traffic environment arises. In this paper, we develop a safety performance function that can reflect the traffic characteristics in detail with an aggregate unit for one hour in addition to the daily model used in the previous studies. As part of the present study, we also perform a comparison and evaluation between models. The safety performance function for daily and hourly units is developed using a negative binomial regression model with the number of accidents as a dependent variable. In addition, the optimal negative binomial regression model for each of the hourly and daily models was selected, and their prediction performances were compared. The model and evaluation results presented in this paper can be used to determine the risk factors for accidents in the highway section considering the dynamic characteristics. In addition, the model and evaluation results can also be used as the basis for evaluating the availability and transferability of the hourly model.

• Journal of IKEEE
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• v.25 no.4
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• pp.728-734
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• 2021

In recent years, there has been a strong interest in the end-to-end autonomous driving based on deep reinforcement learning. In this paper, we present a reward function of latent SAC deep reinforcement learning to improve the longitudinal driving performance of an agent vehicle. While the existing reward function significantly degrades the driving safety and efficiency, the proposed reward function is shown to maintain an appropriate headway distance while avoiding the front vehicle collision.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4A
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• pp.301-309
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• 2002

In this paper, we propose the effective implementation of various nonlinear combiners using by PS-LFSR: m-parallel memoryless-nonlinear combiner, m-parallel memory-nonlinear combiner, m-parallel nonlinear filter function, and m-parallel clock-controlled function. Finally, we propose m-parallel LILI-128 stream cipher as an example of the parallel implementation, and we determine its cryptographic security and performance.