• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.12 no.3
• /
• pp.53-64
• /
• 2013

The car-following model is one of core models in Advanced Vehicle & Highway Systems (AVHS). The car-following model has been developed in aspects such as human factor and reduction error rates. However, the consideration of safety depending on weather condition has not been completed yet. In this paper, therefore, changes of driving condition for car-following due to different road condition were dealt with, and optimal safety distance corresponding to road condition such as dry, wet and snowy were computed. The GMIT(GM Model with Instantaneous T) model was picked over for simulation of adaptive cruise control applied the suggested optimal safety distance. As the results, the 1.7 times longer safety distance was required for wet road condition than dry road condition, and the 5.6 times longer safety distance was required for snowy road condition.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.14 no.4
• /
• pp.86-94
• /
• 2015

In recent days, a Connected Car has caught an attention of the motor companies and various industrial institutes such as communication company. An automobile is regarded as a device and has been developed as an interactive system because the system is connected with various device. This drives a new business item, too. As a new automatic car technology is emerging, a new type of car accident is appeared, too. So, many researches for preventing car accident comes from the driver's are carried out in many car related institutes. In this paper, we study a driver's driving workload and develop an algorithm that measures the driver's driving behavior. We can see that the developed algorithm runs well by the experiment of road test. This results affects various road condition, driver's driving behavior and load that reflects the driver's status.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.4
• /
• pp.13-29
• /
• 2020

Automobiles have long been an essential part of daily life, but the social costs of car traffic accidents exceed 9% of the national budget of Korea. Hence, it is necessary to establish prevention and response system for car traffic accidents. In order to present a model that can classify and predict the degree of injury in car traffic accidents, we used big data analysis techniques of K-nearest neighbor, logistic regression analysis, naive bayes classifier, decision tree, and ensemble algorithm. The performances of the models were analyzed by using the data on the nationwide traffic accidents over the past three years. In particular, considering the difference in the number of data among the respective injury severity levels, we used down-sampling methods for the group with a large number of samples to enhance the accuracy of the classification of the models and then verified the statistical significance of the models using ANOVA.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.17 no.3
• /
• pp.1-17
• /
• 2018

Over the past five years (2010-2014), the total number of traffic accidents has decreased from 226,878 to 223,552 with decrease of 0.37 percent each year. The death toll has also decreased from 5,505 to 4,762. However, the number of rental car accidents and fatalities has been steadily increased. Despite of its growth, no previous study has been conducted on rental car accident severity. This study analyzed data of 18,050 rental car accidents in South Korea collected from 2010 to 2014 and then processed in order to identify which factors could affect the accident severity. Seventeen factors related to rental car accident severity were grouped into four categories: driver, vehicle, roadways and environment. As a result of the ordered probit model analysis, fourteen variables excluding age, intersection, and day of week were found to affect the severity of rental car accidents. The results of the study summarized as follows. First of all, violation of traffic regulations such as speeding increase the severity of rental car accidents. Secondly, rental accident severity is higher at curved sections of complicated roadway, which the driver's field of view is impaired. The results of this study can be used to reduce the severity of rental car accidents in transportation safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.4
• /
• pp.26-32
• /
• 2016

An autonomous car(driverless car, self-driving car, robotic car) is a vehicle that is capable of sensing its environment and navigating without human input. Autonomous cars can detect surroundings using a variety of techniques such as radar, lidar, GPS, odometry, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. Autonomous cars have control systems that are capable of analyzing sensory data to distinguish between different cars on the road, which is very useful in planning a path to the desired destination. An issue tree, also called a logic tree, is a graphical breakdown of a question that dissects it into its different components vertically and that progresses into details as it reads to the right.Issue trees are useful in problem solving to identify the root causes of a problem as well as to identify its potential solutions. They also provide a reference point to see how each piece fits into the whole picture of a problem. Using Issue-Tree menthods, transportation safety policies were developed with autonompus vehicle in mind.

• Journal of Information Technology Services
• /
• v.15 no.4
• /
• pp.41-62
• /
• 2016

In Internet of Things (IoT) era, more diverse types of information are collected and the environment of information usage, distribution, and processing is changing. Recently, there have been a growing number of cases involving breach and infringement of personal information in IoT services, for examples, including data breach incidents of Web cam service or drone and hacking cases of smart connected car or individual monitoring service. With the evolution of IoT, concerns on personal information protection has become a crucial issue and thus the risk analysis and management method of personal information should be systematically prepared. This study shows risk factors in IoT regarding possible breach of personal information and infringement of privacy. We propose "a risk analysis framework of protecting personal information in IoT environments" consisting of asset (personal information-type and sensitivity) subject to risk, threats of infringement (device, network, and server points), and social impact caused from the privacy incident. To verify this proposed framework, we conducted risk analysis of IoT services (smart communication device, connected car, smart healthcare, smart home, and smart infra) using this framework. Based on the analysis results, we identified the level of risk to personal information in IoT services and suggested measures to protect personal information and appropriately use it.

• Journal of Information Technology Services
• /
• v.22 no.3
• /
• pp.49-63
• /
• 2023

The inclusion of software and wireless communication devices in vehicles has raised concerns regarding automobile security. In its response, UNECE WP.29 implemented the first-ever international standard for automotive cyber security in June 2020. Yet, the existing disparity between national standards for automotive certification systems and 「UN Regulation No. 155」 has caused confusion among auto makers. This discrepancy not only jeopardizes the security of domestic vehicles but also poses challenges to the seamless import and export of automobiles. Hence, there is a need to enhance the automotive cyber security certification system; however, there is a dearth of scholarly discourse on this topic. Consequently, this study presents a proposal for enhancing the domestic automotive cyber security certification system. In view of this, existing legal frameworks such as the 「Motor Vehicle Management Act」 and the 「Self-Driving Vehicle Act」 were reviewed, along with domestic and international automotive certification systems. The recommendations for improvement, derived from the findings, encompass institutional, legal, and operational aspects. This study is highly significant as it examines both domestic and international automotive certification systems in an area where there is a lack of academic discussion.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.14 no.4
• /
• pp.52-61
• /
• 2015

PCE(Passenger Car Equivalents) is used to analysis of road capacity and LOS(Level of Service). In this study calculates PCE by number of lane and 12 vehicle type by MOLIT(Minister of Land, Infra Structure and Transport) using individual vehicle data. The results of the calculation, PCEs are increased when high vehicle classification level, many number of lanes and weekend. Heavy vehicle factors are smaller than KHCM on 4, 6 lane. Also, In this study estimates of PCE variation model by heavy vehicle percentage. Impact of Heavy vehicles on PCEs is the most sensitive on 2 lane. The results of the study, heavy vehicles low impact on PCE on multi-lane and business trips are a little in weekend.

• Journal of Information Technology Services
• /
• v.12 no.2
• /
• pp.171-184
• /
• 2013

Frequently faced with dangerous situations, for evidentiary purpose in case of civil and criminal liability challenges, car drivers in Korea have been armed with so-called 'black boxes'; however, which are just video recorders in vehicles rather than real 'black boxes' that are equipped in the airplanes. In the United States, they are called EDRs(Event Data Recorders), more technically, which means that they record data of events happened while driving, such as velocity changes, airbags deployment, seatbelt wearing etc. just like in the airplanes. EDR technology is quickly becoming more advanced, more widely available, and less expensive; however, new concerns are emerging : the privacy of drivers. In U. S., vehicle manufacturers and insurance companies and the governmental agencies including the courts and legislatures are the main parties in terms of the EDR concerns. In order to determine the best way to regulate EDR, it is necessary to balance all the merits, such as safety, privacy, truth, justice and efficiency, to support a legal framework regulating the EDR concerns. This article, in light of the regulation of EDR and experience therof in the United States, examines EDR technology itself, particularly with respect to the automobile industry, describing its history, its current state, and trends that may change it in the future; and explains how the National Highway Transportation Safety Agency (NHTSA), legislatures, courts have approached EDR data. At the early stage of regulation on EDRs in Korea, examining U. S. legal framework and usages would help for successful establishment of legislation and regulation.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.4
• /
• pp.1-12
• /
• 2017

Traffic accidents are caused by a combination of human factors, vehicle factors, and environmental factors. In the case of traffic accidents where rental cars are involved, the possibility and the severity of traffic accidents are expected to be different from those of other traffic accidents due to the unfamiliar environment of the driver. In this study, we developed a model to forecast the severity of rental car accidents by using Naive Bayes classifier for Busan, Gangneung, and Jeju city. In addition, we compared the prediction accuracy performance of two models where one model uses the variables of which statistical significance were verified in a prior study and another model uses the entire available variables. As a result of the comparison, it is shown that the prediction accuracy is higher when using the variables with statistical significance.