This study analyzed the impact of improvements to the driver’s license system for elderly drivers on the incidence of traffic accidents. As South Korea’s population ages, the number of licensed drivers aged 65 years and older has surpassed 4.5 million as of 2024, accounting for approximately 15% of all license holders. Traffic accidents involving elderly drivers have increased steadily and tend to be more severe than those involving younger drivers. In response, the Road Traffic Act was amended in 2019 to shorten the license renewal cycle for drivers aged 75 and older, mandate dementia screening, and require traffic safety education. This study compared traffic accident statistics before and after the policy change (2018 and 2023) and used consulting data from 617 elderly drivers to examine the relationships between driving time, frequency, distance, and potential accident risk factors using a negative binomial regression analysis. The results show that after the policy changes, the number of traffic accidents per 10,000 elderly drivers decreased by up to 20.4%, demonstrating the effectiveness of the reforms. Furthermore, increased driving time, frequency, and distance were all significantly associated with a higher accident risk, whereas older age was linked to fewer accidents, likely owing to self-regulation among elderly drivers. Policy recommendations include limiting continuous driving time to 60 min, encouraging regular breaks, enhancing tailored safety education, tightening license aptitude test standards, and supporting the adoption of advanced safety features in vehicles. This study is expected to contribute to the development of effective policies to reduce traffic accidents among elderly drivers and create a safer traffic environment.

With the rapid expansion of personal mobility (PM) devices as urban transport alternatives, the associated safety risks have increased significantly. Although previous studies have offered insights into user behavior and accident traits, more integrated approaches that consider spatial and administrative contexts are required to better understand the factors affecting accident severity. This study investigated the factors influencing accident severity involving PM devices in Seoul, South Korea by employing a cross-classified multilevel model (CCMM) to account for both police jurisdiction and regional characteristics. Analyzing the 2021 data from the Traffic Accident Analysis System (TAAS), the model showed strong validity (ICC: 15.8%, DIC: 697.2), outperforming the logistic and hierarchical models. Key predictors of higher severity included crashes in non-standard areas (e.g., other than single roads or intersections), helmet non-use, and older age of victims and perpetrators. Violations, such as exceeding passenger capacity, were negatively associated with severity. Industrial areas and high subway station densities reduced the severity, reflecting the benefits of pedestrian-friendly infrastructure. Larger areas covered by police officers significantly increased the severity, revealing enforcement limitations. The 2021 Road Traffic Act revision has had no statistically significant impact. These results highlight the need for integrated policies that combine infrastructure improvements, enhanced enforcement, and behavioral changes to reduce the severity of PM-related accidents in urban environments.

관상학(Physiognomy)은 오랜 역사에도 불구하고 경험적 검증의 부재로 미신 으로 치부되어 왔으나, 일부 실용 분야에서는 활발히 참조되어 이론과 실제 간의 괴리가 존재했다. 이에 본 연구는 ‘외형이 내면을 반영한다’는 관상학의 핵심 전제를 현대 통계 방법론으로 실증적으로 검증하고자, MBTI의 감정형 (F)-사고형(T) 유형과 관상학적 얼굴 특징 간의 상관관계를 분석하였다. 총 77 명의 참여자로부터 사진 데이터를 수집하여, 관상학 이론에 기반한 6가지 얼 굴 특징(눈 크기, 눈동자 크기, 코끝의 살, 입술 두께 등)을 전문가와 함께 5점 척도로 코딩하였다. 수립된 가설을 검증하기 위해 선형 및 로지스틱 회귀분석 을 적용하였다. 분석 결과, F/T 유형은 ‘눈길이’를 제외한 5가지 특징에서 유의미한 차이를 보였으며, 감정형(F) 집단이 더 큰 눈, 도톰한 입술 등을 갖는 경향을 나타냈 다. 또한, F/T 유형을 예측하는 로지스틱 회귀 모델(Pseudo R²=.462)에서는 ‘눈 동자 크기’, ‘코끝의 살’, ‘입술 두께’가 통계적으로 유의미한 핵심 예측 변수로 확인되었다. 본 연구는 관상학적 특징과 성격 유형 간의 실증적 연관성을 규 명함으로써, 관상학을 탈신비화하고 과학적 탐구의 대상으로 전환할 수 있는 가능성을 제시하며, 이는 관상학이 향후 심리학, 인공지능 등과 융합될 수 있 는 토대를 마련했다는 점에서 학술적 의의를 지닌다.

This study aims to model an accident that occurred at building demolition work sites in Gwangju in 2021 by using functional resonance analysis method(FRAM) and to understand a range of factors contributing to the accident based on the concepts and principles of FRAM and Safety-II. The nature of building demolition works needs to be understood from the viewpoint of socio-technical systems. Not only technical factors but also non-technical factors, including human, organizational, and political factors, and their complicated interrelationships should be considered in the modeling and analysis of accidents happening in the works. Because of the inherent complexity of a demolition works, it is unlikely to specify all of the necessary activities to be conducted in the works and their accountable actors. Additionally, unexpected situations are likely to happen and therefore some activity procedures cannot be followed in a prescribed way, which means that workers sometimes should conduct their activities in an improvisional way. Those characteristics of building demolition works indicate that a traditional accident analysis method based on a linear cause-effect relationship would be inadequate, and that more systemic approaches that can deal with the socio-technical complexities and characteristics of demolition works should be used. With this in mind, we applied FRAM to the accident happening in Gwangju in 2021 and attempted to understand the accident based on the concepts and principles of FRAM and Safety-II (e.g. a functional variablity and its propagation to another function). Lastly, we also suggested ways to enhance the safety of building demolition working sites.

This study focuses on analyzing the impact range of toxicity, overpressure and radiant heat (pool fire and boiling liquid expanding vapor explosion, BLEVE) resulting from a propylene oxide leakage accident and proposes mitigation strategies to minimize damage. A risk assessment was conducted by designing accident scenarios based on variables such as substance quantity and wind speed. The results indicated that toxicity and BLEVE were the primary risk factors, and the risk level increased as the substance quantity increased and wind speed decreased. For future mitigation strategies, it is suggested that a quantitative analysis of vapor dispersion rates and dilution and effects under various environmental conditions be conducted, along with preliminary research on optimizing absorbents and catalytic materials.

This study aims to utilize the AcciMap accident investigation method to compare and analyze the causes and mechanisms of chemical and laboratory accidents, ultimately proposing effective management strategies for accident prevention. Despite the establishment of safety management frameworks through the “Laboratory Safety Environment Creation Act” in South Korea, laboratory accidents continue to occur frequently due to the inherent variety and unpredictability of hazards in research environments, highlighting the need for mandatory root cause analysis. Accordingly, the analysis was conducted using the accident investigation method AcciMap and the software tool VOSviewer. Based on these findings, this study proposes tailored management strategies for chemical and laboratory accidents. For chemical accidents, strengthening safety systems and conducting regular maintenance are critical. For laboratory accidents, implementing safety education programs to enhance researchers’ safety awareness and providing appropriate equipment for experimental environments are essential. Moreover, the study emphasizes the necessity of mandating root cause analysis for laboratory accidents to systematically identify accident causes and develop effective preventive measures. Finally, leveraging the accident reporting system outlined in the Laboratory Safety Act is essential to ensure prompt, transparent responses and structured management in the event of accidents.

In this study, we aim to classify personal mobility (PM)-related traffic crash data into four categories: PM-to-vehicle, PM-to-pedestrian, PM-single, and vehicle-to-PM crashes, and analyze the factors influencing the severity of each crash type. To overcome the limitations of existing studies in explaining the impact of independent variables on ordinal dependent variables, a random forest model was combined with the Shapley additive explanation technique. This approach visualizes the influence of independent variables on a dependent variable, providing clearer insights and enhancing interpretability. The analysis of PM traffic accidents, categorized into at-fault, single-vehicle, and victim accidents, revealed distinct key factors for each type. The main contributors to the severity of crashes caused by PM are traffic violations by teenagers and collisions with elderly pedestrians. Single-vehicle accidents were predominantly caused by overturn incidents, with inadequate driving skills among PM users aged 40 years and older, and significantly increasing severity. Victim accidents primarily occur at intersections, where the behavior of the at-fault driver and age of the PM user are critical factors influencing the severity. We identified various factors influencing the severity of PM crashes by type, highlighting the need for tailored policy measures. Proposed policies include physically separating bicycle–pedestrian shared spaces and strictly regulating illegal PM sidewalk riding, introducing PM licenses for teenagers to ensure compliance with traffic rules, and implementing regular safety education programs for all age groups. Although this study applied a new analytical technique, it relied on limited crash data, thus limiting the results to estimates.

This study collected video footage of accident-risk scenarios on actual roads using automobiles and motorcycles. A total of 191,500 km was driven with three vehicles and one motorcycle, capturing 6,550 near-miss accident videos. The footage was analyzed and categorized based on the 27 parameters of the iGLAD(Initiative for the Global Harmonization of Accident Data) accident categories. Parameters difficult to classify under iGLAD were localized to fit domestic conditions, and further analysis identified areas needing optimization. The categorized data was organized into a web-based database platform, providing statistical analysis and search functions for scenario development. Future use of this data will support the creation of safety evaluation scenarios for autonomous vehicles, enhancing traffic accident investigation and analysis systems. Expanding the database to include data from secondary roads and parking areas is expected to increase its applicability and value.

This study analyzed actual traffic accident data to select humans’ unavoidable accidents and to examine whether avoidance is possible after AEBS(Advanced Emergency Braking System) is applied to these accidents. In cases where avoidance is not possible with AEBS, those accidents were determined to be examples where V2X(Vehicle-to-Everything) technology is necessary. Subsequently, by applying V2V(Vehicle-to-Vehicle) and V2I(Vehicle-to-Infrastructure) communication technologies, this research analyzed the possibility of accident avoidance. The results confirmed that the application of V2X technology enables accident avoidance. Additionally, by applying various variables, it identified limitation scenarios that cannot be resolved by V2X technology, and discussed strategies for accident avoidance in such situations.

This study systematically analyzed the causes of recurring electric shock accidents using accident analysis techniques and attempted to suggest implications for accident prevention. 124 electrocution death accidents that occurred from 2017 to 2022 were analyzed and classified into four factors(organizational influence, unsafe supervision, preconditions for unsafe acts, and unsafe acts) using the HFACS technique. As a result, First, in terms of organizational influence, many issues related to organizational processes were found, and the main causes were the lack of a safety management manual for electrical work, the lack of risk assessment, and the lack of safety procedures for electrical work. Second, in terms of unsafe supervision, the main causes were inappropriate operations such as not assigning a work supervisor during work or the lack of actual management and supervision. Third, in terms of preconditions for unsafe acts, the main causes were physical and technical problems such as not performing power outage work or not taking protective measures for live parts. Fourth, in terms of unsafe acts, the main causes were analyzed to be violations of safety procedures such as workers mistaking a power outage or not recognizing a current leakage condition, making a wrong judgment of the situation, and shortening the work time and working without safety measures for work convenience. Additionally, when examining whether the personal characteristics of those who died from electric shock had significant differences in unsafe behaviors, it was confirmed that there were significant differences in violations or decision-making errors depending on the industry and electrical-related major.

This study aimed to investigate the factors affecting the severity of taxi traffic accidents at intersections in Busan and propose measures to improve traffic safety. This study collected data on taxi traffic accidents that occurred at intersections in the Metropolitan City of Busan during the past 3 years (2020–2022) from Traffic Accident Analysis System(TAAS) and road views, and analyzed factors affecting their severity by employing an ordered probit model. The severity of taxi traffic accidents worsened with violations of (among others) traffic signals and pedestrian protection during January, April, and September. In addition, when a major street was operated with a permissive left turn, the severity of taxi traffic accidents worsened. Measures to improve traffic safety suggested in this study included safety education that focused on particular violations for taxi drivers, mandatory education for transport employees in an experiential format, support of video storage devices for driving records, policy establishment for the promotion and certification of good and bad driving videos, time adjustment of joint safety management inspection, and left-turn signal operation with an unprotected system and P-turn guidance.

This study aimed to analyze the impact of implementing a voluntary driver's license return program on reducing traffic crashes for older drivers who were previously involved in traffic accidents. The traffic crashes caused by elderly drivers were categorized by crash type. We used the Chi-square test to compare municipalities that implemented the program in 2019 and 2020 with those that did not and explored variations in crash types based on the residential areas and age groups of elderly drivers. The voluntary driver's license return program reduced considerably the number of single-vehicle crashes involving elderly drivers. Moreover, while all crash types decreased in rural areas, only pedestrian–vehicle, and single-vehicle crashes were reduced considerably in urban areas. In terms of age groups, drivers aged >75 years were associated with reduced numbers of crashes (all types). Similarly, the 70–74 age group demonstrated considerable reductions in pedestrian–vehicle and single–vehicle crashes, emphasizing the importance of encouraging and supporting license returns among these age groups. First, because the characteristics of each crash type vary, it is important to analyze the impact of voluntary driver’s license returns on crash reduction, with a focus on specific crash types. Second, voluntary license returns should be promoted in all regions. However, in rural areas with limited access to public transportation, mobility must be supported by the introduction of DRT. Third, given that drivers aged >75 years were associated with reduced numbers of crashes (for all types of crashes), priority policies should be implemented to encourage license returns within this age group, along with tailored incentives. However, as the voluntary license return program is intended to support selfinitiated cessation of driving without compulsion, strategies should also be explored to promote voluntary returns without age restrictions. Fourth, a standardized evaluation system should be established to enable older drivers to assess their driving abilities and physical conditions, further encouraging voluntary license returns.

This study aimed to statistically analyze and understand the factors contributing to road icing accidents on Korean roads, particularly within sections designated as ice-prone. The objective was to assess the adequacy of the existing criteria for designating these sections and to provide insights for improving safety measures on icy roads. Road icing accident data were collected from Korea’s (traffic accident analysis system (TAAS) database, covering incidents from 2018 to 2022 on both expressways and general roads. The data were compiled to create a comprehensive database that incorporated geographic and weather-related factors influencing road icing accidents. Using geographic information systems (GIS), a spatial analysis was performed on the designated ice-prone and non-designated sections. The inverse distance weighting (IDW) method was applied to interpolate the meteorological data, and the temperature lapse rate was used to adjust for altitude-related variations in temperature, providing estimates for conditions such as the average temperature, relative humidity, and precipitation days at each accident location. The analysis revealed that only 2.9% of designated ice-prone sections reported icing-related accidents, whereas 97.6% of icing accidents occurred in non-designated sections. This discrepancy highlights potential gaps in the current criteria for designating ice-prone areas. Additionally, road characteristics such as traffic volume, lane count, speed limit, and curve radius, along with meteorological factors such as humidity, precipitation frequency, and solar radiation exposure, were observed to be significantly correlated with icing accidents. Regions with high relative humidity and low sunlight exposure exhibited a heightened risk of road icing accidents, suggesting the need for these parameters to designate ice-prone sections. This study underscores the need to refine Korea's criteria for designating ice-prone sections by incorporating a wider range of risk factors, including detailed terrain data, shaded areas, and road geometry factors, such as slopes. Integrating these additional elements into the designation process could enhance the precision and effectiveness of preventive measures and ultimately reduce the risk of icing-related accidents in Korea’s road networks. These findings provide a foundation for future policy and management decisions to enhance road safety during the winter.

Recently, the number of elderly driver accidents has been steadily increasing. EDR(Event Data Recorder) helps a lot in understanding traffic accidents. In particular, as anxiety about SUA(Sudden Unintended Acceleration) increases, EDR data is playing an important role in accident analysis. In this study, EDR data of an accident vehicle suspected of SUA was analyzed to identify traffic accident circumstances and detailed accidents. Experimental results were derived and analyzed by simulating the situation of SUA while driving a car. As a result, it was found that normal braking is performed when the brake pedal is operated even in dangerous situations such as mechanical defects and driver malfunctions. Rather than finding the cause of an accident after a traffic accident, countermeasures are needed to prevent mechanical defects and driving malfunctions before a traffic accident.

PURPOSES : This study aimed to investigate the factors affecting the severity of traffic crashes caused by personal mobility (PM) devices compared with those involving victims. METHODS : Traffic crashes involving PM devices were used to build a non-parametric statistical model using a classification tree. Based on the results, the factors influencing both at-fault and victim-related crashes caused by PM devices were analyzed. The factors affecting accident severity were also compared. RESULTS : Common factors affecting the severity of traffic crashes involving both perpetrators and victims using PM devices include occurrences at intersections, crosswalks at intersections, single roads, and inside tunnels. Traffic law violations by PM device users (perpetrators) influence the severity of crashes. Meanwhile, factors such as the behavior of perpetrators using other modes of transportation, rear-end collisions, road geometry, and weather conditions affect the severity of crashes where PM device users are the victims. CONCLUSIONS : To reduce the severity of traffic crashes involving PM devices, it is essential to extend the length of physically separated shared paths for cyclists and pedestrians, actively enforce laws to prevent violations by PM device users, and provide systematic and regular educational programs to ensure safe driving practices among PM device users.

PURPOSES : According to government data, the Black Spot Program has resulted in an average 28.8% reduction in traffic accidents within one year of project implementation in areas where road conditions improved. However, there has been a lack of in-depth analysis of the midto- long-term effects, with a predominant focus on short-term results. This study aimed to analyze the mid-to-long-term effects of the Black Spot Program to assess the sustainability of its reported short-term impact. Additionally, the differences in the mid-to-long-term effects were investigated based on the scale of traffic accidents at intersections and the characteristics of these effects are revealed. METHODS : The mid-to-long-term effects of the Black Spot Program were analyzed at 122 intersections in Seoul, Korea, where the program was implemented between 2013 and 2017, using traffic accident data spanning five years before and after implementation. Additionally, the differences in the program's effects were analyzed at the top-100 intersections with the highest traffic accident concentration in Seoul using the chi-square test to identify these differences. To theoretically validate these differences, the Hurst exponent, commonly used in economics, was applied to analyze the regression to the mean of the intersections and reveal the correlation with improvement. RESULTS : Through the Black Spot Program at 122 intersections, a 33.3% short-term accident reduction was observed. However, the midto- long-term effect analysis showed a 25.8% reduction, indicating a slightly smaller effect than previously reported. Specifically, the top-100 intersections exhibit a 15.4% reduction. A chi-square test with a 95% confidence level indicated significant differences in the program’s effects based on the scale of traffic accidents at intersections. The Hurst index (H ) was measured for the top-100 intersections, yielding H = 0.331. This is stronger than the overall H = 0.382 for all intersections in Seoul, suggesting that the regression to the mean is more pronounced, which may lead to a lower effectiveness of the improvement. CONCLUSIONS : The mid-to-long-term effects of the Black Spot Program were relatively lower than its short-term effects, with larger differences in effectiveness observed based on the scale of traffic accidents at intersections. This indicates the need to redefine the criteria for selecting project targets by focusing on intensive improvements at intersections, where significant effects can be achieved.