Conventional fixed-time traffic signal operations at urban intersections are typically based on prescheduled plans that presume stable and recurring traffic patterns, particularly during peak commuting hours. However, recent societal changes—including flexible work schedules, telecommuting, and evolving workweek structures—have introduced greater variability in traffic demand, thereby diminishing the effectiveness of traditional peak-hour-focused control strategies. This study investigated the performance of an AI-based adaptive traffic signal control system that operated independently of predefined time plans. A field demonstration was conducted in Jeju City, South Korea, where the system was deployed in both the cyclic and acyclic operation modes. By leveraging real-time traffic data obtained from AI-enabled video detectors, the system adjusted the signal timings on a per-second basis in response to dynamic traffic conditions. The performance was evaluated against the conventional time-of-day (TOD) control method under diverse traffic scenarios, including typical weekdays, weekends, and local event days. The AI-based system achieved substantial reductions in intersection delays—24.3% on weekdays, 22.2% on weekends, and 17.1% on event days—compared with the TOD baseline. Moreover, it preserved a comparable level of traffic progression (measured by the proportion of non-stop vehicle flows) even during acyclic operations. The greatest efficiency gains were observed during the nighttime and low-traffic periods, underscoring the capacity of the system to minimize unnecessary delays under variable conditions. These results highlighted the potential of AI-based adaptive signal control as a viable alternative to conventional fixed-time operations, offering enhanced responsiveness and operational flexibility in increasingly complex urban traffic environments. Future research will focus on scaling the system to larger networks and developing integrated optimization strategies across multiple intersections.

This study aims to analyze the mitigation effects of phantom traffic jams on highways in a mixed traffic environment in which autonomous vehicles (AVs) and human-driven vehicles coexist. It focuses on identifying the key factors that contribute to phantom congestion and evaluating the extent to which the introduction of AVs can stabilize traffic flow and alleviate nonrecurring congestion. To achieve this goal, a theoretical analysis was conducted to examine the major causes of phantom traffic jams, including variations in the vehicle speed, road gradients, driver behaviors (for example, acceleration and deceleration), and visual adaptations in tunnel sections. Based on these factors, simulation scenarios were constructed using VISSIM to replicate real-world conditions in highway tunnel segments. The scenarios varied according to the AV penetration rate (0%, 20%, 40%, and 60%) and incorporated key traffic indicators such as the vehicle composition, speed, and headway. Traffic flow stability was evaluated using metrics including the average travel speed, headway consistency, and frequency of acceleration and deceleration events across sections. The simulation results showed that as the proportion of AVs increased, the average travel speed improved, and both the headway stability and flow continuity were enhanced. In particular, tunnel segments with higher AV ratios experienced fewer deceleration events and reduced behavioral variability, contributing to a more stable traffic flow. These findings suggested that AVs could play a critical role in mitigating phantom traffic jams by maintaining steady speeds and safe following distances, thereby reducing the instability caused by human driving behaviors. This study offers a foundational reference for future traffic congestion mitigation strategies and AV policy development, particularly in anticipation of increasingly mixed traffic environments.

해상교통안전법 제30조 제1항에 따라 국내에 설정된 지방해양수산청장의 고 시에 따르면, 대부분의 경우 해상교통안전법 제75조의 통항분리수역에서의 항 법에 따라 통항하도록 규정하고 있다. 따라서 해상교통안전법이 규정하고 있는 해상교통관리체계의 기본구조는 동 법 제75조에서 규정하는 통항분리제도를 근간으로 한다. 해상교통안전법 제75조의 핵심 법리는 다음과 같다. 먼저, 통항분리수역에서 선박충돌의 위험이 발생한 상황에서는 어떠한 선박의 경우에도 ‘절대적이고 우선적 권리(absolute and priority rights)’를 주장하지 못하며, 통 항분리수역 안의 통항로를 따라 항행하는 선박의 경우에도 위 원칙의 예외일 수 없다. 따라서 통항분리수역을 따라 항행하는 선박의 경우에도 적절한 경계 의 수행, 주변 교통환경의 지속적 관찰, 적절한 속력의 유지를 통해 충돌위험 을 사전에 예방할 의무를 부담한다. 둘째, 명문 규정의 부재에도 불구하고 통 항분리수역에는 해상교통안전법 제75조와 다른 일반항법 규정이 중첩적으로 적용된다고 볼 것이다. 따라서 통항로를 따라 진행하는 선박과 횡단선박 사이 에는 선박들의 조우관계에 따라 해상교통안전법 제5장에서 정하는 일반항법이 적용될 것이므로, 각 선박은 일단 형성된 조우관계에 적용되는 항법에 따라 운 항할 책무를 부담한다. 셋째, 통항분리수역에서는 부득이한 사유가 없는 한 통 항로의 횡단은 원칙적으로 금지되지만, 통항로를 따라 항행하는 선박에 대해서 도 적절한 견시의무의 수행, 안전한 속력으로의 항행 등 항법 일반의 요구가 면제되지 않는다. 다만, 통항분리수역에서는 어로작업에 종사하고 있는 선박, 길이 20미터 미만의 선박, 범선을 제외한 일반 선박에는 통항불방해 의무를 부 과하고 있지 않으므로, 통항로를 따라 항행하는 선박은 통항불방해 의무가 없 는 횡단선박에 대하여 통항 우선권이 없는 것으로 보아야 한다. 한편 해양수산 관서는 우리 영해 내에 설정된 통항분리수역 등에 관한 정보를 외국선박의 조 선자 등에게 적절히 인식시키는 노력을 기울여야 할 것이고, 이들 수역에서의 항법도 가능한 한 승인된 국제표준에 부합되도록 설정하여야 한다.

Efficient yet realistic ship routing is critical for reducing fuel consumption and greenhouse-gas emissions. However, conventional weather-routing algorithms often produce mathematically optimal routes that conflict with the paths mariners use. This study presents a hybrid approach that constrains physics-based weather routing within an AISderived maritime traffic network (MTN) built from one year of global Automatic Identification System data. The MTN represents common sea lanes as a graph of approximately 10,956 waypoints (nodes) and 17,561 directed edges. Using this network, an optimal low-emission route is computed via graph search and then compared against both a traditional unconstrained route and an advanced weather-routing model (VISIR-2). In a May transitionseason case (Busan–Singapore voyage), the AIS-constrained route reduced fuel consumption and CO₂ emissions by about 1.9% relative to the fastest feasible route, while closely following real traffic corridors (over 90% overlap with actual 2024 AIS tracks). While this 1.9% saving does not reach the high-end potential of an unconstrained, state-of-the-art model like VISIR-2 (which can demonstrate double-digit savings in certain conditions), it is achieved with an increase in transit time of ~6.5 h (≈3.2%). This represents a crucial trade-off, prioritizing operational realism and adherence to real-world traffic corridors over maximum theoretical efficiency.

The primary objective of the study is to analyze and evaluate the situation and trends of inland waterway traffic accidents in Vietnam from 2017 to 2024. The study employs reliable secondary data sources, which are analyzed using statistical methods and heatmap applications to examine and assess trends in inland waterway traffic accidents in Vietnam. The results indicate a steady increase in both the number and scale of inland waterway accidents nationwide over the years. Additionally, the accident-prone areas in key inland waterways will be identified. Based on these findings, the research team has proposed recommendations and solutions aimed at improving traffic safety on Vietnam's inland waterways.

As conventional road traffic noise prediction models are designed to estimate long-term representative noise levels, capturing fine-scale noise fluctuations caused by real-world traffic dynamics is challenging. A previous study proposed a microscopic road traffic noise model (MTN) can calculate time-series noise levels with a resolution of 1 s using the concept of a moving noise source. In this study, two experiments were conducted to verify the accuracy of the noise prediction of the model. First, by comparing the calculated noise levels of two conventional road traffic noise models and the MTN in a simple road simulation environment, it was confirmed that the calculation error was within 3 dB(A) when calculating the 1-h equivalent noise level. Second, an experiment was conducted to verify the noise prediction error of the MTN on six actual roads. A comparison of the calculated noise level using the MTN based on traffic data collected from actual roads with the measured noise level on real roads showed that the calculated noise level achieved a mean absolute error (MAE) of 1.88 dB(A) from the equivalent noise level and 1.28 dB(A) from the maximum noise level. This was similar to the MAE of the foreign road traffic noise models. However, when the location of the receiver is within 10 m of the road, an error of more than 3 dB(A) occurs because of the simplicity of the MTN propagation model, which remains a problem that must be solved in the future. This study proved that the noise level calculation using the MTN is similar to the noise of an actual road environment. Additionally, the continuous development of the MTN is expected to make it an effective alternative for the management of road noise.

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.

This study aimed to evaluate the effect of key operational factors on traffic performance in long underground expressways. This study was motivated by the increasing policy interest in underground expressway infrastructure as a solution to chronic surface-level congestion in dense urban regions. A scenario-based microscopic traffic simulation was conducted using VISSIM considering combinations of traffic volume, proportion of heavy vehicles, and longitudinal slopes. A total of 72 scenarios were simulated, and the weighted average speed and total throughput were analyzed. The simulation results showed that the entry traffic volume and longitudinal gradient significantly affected the average speed, particularly in uphill exit segments. The heavy vehicle ratio also contributed to consistent reductions in speed. However, the overall throughput remained relatively stable despite variations in heavy vehicle proportions, suggesting that speed is more sensitive to flow composition than to volume capacity. Although interaction effects were not statistically tested, the combined scenario trends suggested that steeper slopes and high heavy-vehicle ratios jointly intensify speed reduction. These findings support the early-stage design and traffic planning of underground expressways.

This paper presents a novel methodology for assessing the vulnerabilities of autonomous vehicles (AVs) across diverse operational design domains (ODDs) related to road transportation infrastructure, categorized by the level of service (LOS). Unlike previous studies that primarily focused on the technical performance of AVs, this study addressed the gap in understanding the impact of dynamic ODDs on driving safety under real-world traffic conditions. To overcome these limitations, we conducted a microscopic traffic simulation experiment on the Sangam autonomous mobility testbed in Seoul. This study systematically evaluated the driving vulnerability of AVs under various traffic conditions (LOSs A–E) across multiple ODD types, including signalized intersections, unsignalized intersections, roundabouts, and pedestrian crossings. A multivariate analysis of variance (MANOVA) was employed to quantify the discriminatory power of the evaluation indicators as the traffic volume was changed by ODD. Furthermore, an autonomous driving vulnerability score (ADVS) was proposed to conduct sensitivity analyses of the vulnerability of each ODD to autonomous driving. The findings indicate that different ODDs exhibit varying levels of sensitivity to autonomous driving vulnerabilities owing to changes in traffic volume. As the LOS deteriorates, driving vulnerability significantly increases for AV–bicycle interactions and AV right turns at both signalized and unsignalized intersections. These results are expected to be valuable for developing scenarios and evaluation systems to assess the driving capabilities of AVs.

This study aims to evaluate traffic safety facilities in school zones in Busan Metropolitan City through Importance-Performance Analysis. This study investigated the traffic safety facilities in nine school zones, which have relatively more traffic accidents in Busan Metropolitan City from 2020 to 2022, through a field study and an Analytic Hierarchy Process(AHP). It identified their performance(i.e., compliance rate) and importance to derive measures for the improvement of traffic safety facilities in school zones. The field study showed that the compliance rate of starting points among traffic safety signs was low, and no speed limits were complied with the installation regulations among traffic road markings, but road safety facilities were generally well managed and operated. As a result of AHP, the order of importance was road safety facilities, traffic safety signs, and traffic road markings. More specifically, speed bumps, safety signs, and crosswalks were found to be more important than others in road safety facilities, traffic safety signs, and traffic road markings, respectively. Importance- Performance(compliance) Analysis revealed that the traffic safety facilities necessary to be most urgently improved are starting points. This result can be resorted to underlying measures to determine priorities for installing and operating traffic safety facilities in school zones.

This study evaluated the safety impact of automated traffic enforcement cameras targeting tailgating behavior at signalized intersections by comparing traffic conditions shortly after installation and one year later. The Kukkiwon intersection in Gangnam-gu, Seoul, South Korea was selected as the study site. Individual vehicle speeds, accelerations, and subsequent distances were extracted from video data using YOLOv8 and ByteTrack, which are advanced deep learning-based object detection and tracking algorithms. Surrogate safety measures (SSM), such as time to collision (TTC), modified time to collision (MTTC), and proportion of stopping distance (PSD), were calculated to assess changes in traffic safety. Every SSM indicated an improvement one year after the installation of enforcement cameras, suggesting a reduction in collision risks. In particular, the PSD indicator showed a notable improvement, reflecting a better maintenance of safe following distances. These results highlight the effectiveness of automated enforcement in improving intersection safety and suggest its scalability to other intersections with similar tail-gating issues. Future research should explore the long-term and multisite effects using diverse intersection types and behavioral indicators.

This study quantitatively assess the risk of ice-related accidents on road facilities such as bridges and tunnels, and examines the influence of road facility characteristics on ice-related accidents. Ice-related accident data from expressways and national highways in South Korea were collected over a 10-year period (2013–2022). Geographic information systems (GIS) and node-link systems were employed to classify accidents based on road facility types. The number of ice-related accidents per unit length and per individual segment was examined according to the road classification. Furthermore, the fatality rate and fatality-weighted indicator (FWI) were calculated to evaluate the severity of icerelated accidents.The number of ice-related accidents per unit length of road facilities is higher on national highways than on expressways. For both expressways and national highways, the incidence rate of ice-related accidents on bridges was higher than those on ordinary sections and tunnels. A greater number of ice-related accidents occurred on long-span bridges and tunnels for both road classifications. The fatality rate of ice-related accidents on expressways was approximately 1.5 times higher than that on national highways. The fatality rate of ice-related accidents occurring on road facilities within expressways was approximately three times higher than the overall fatality rate of ice-related accidents on expressways. On national highways, the fatality rate of ice-related accidents on bridges was higher than the overall fatality rate of ice-related accidents, whereas the fatality rate of ice-related accidents in tunnels was lower than that on national highways. The FWI of ice-related accidents on bridges and tunnels was more than twice that on ordinary sections on both expressways and national highways. Among expressway facilities, tunnels exhibited the highest FWI, whereas on national highways, the FWI values for bridges and tunnels were similar. The findings of this study suggest that the influence of road facilities on ice-related accidents should be considered in winter road maintenance strategies. This could contribute to reducing not only the frequency of ice-related accidents, but also the number of fatalities and injuries resulting from such incidents.

도심지에서는 증가하는 교통량으로 인해 지상에서 지하로 교통 시설을 확대하고 있다. 지하에 교통 시설물을 시공할 경 우 기존 도로를 굴착한 후에 지하 시설물을 시공하는 동안에 임시통행판을 사용하여 기존 도로의 역할을 대체하도록 하 고 있다. 이러한 임시통행판은 대부분 철재를 사용하고 있으며 표면에 아스팔트, 콘크리트 등 다양한 재료를 적용하여 사용하기도 한다. 본 연구에서는 콘크리트 슬래브를 임시통행판으로 적용하고 있는 사례를 조사하기 위해 미국 로스앤젤 레스 지역의 콘크리트 임시통행판이 설치된 구간에 대한 현장 조사를 실시하였으며 구성 요소와 손상 유형을 분석하였 다. 콘크리트 임시통행판의 주요 구성 요소로는 각각의 임시통행판을 연결해주는 연결부와 프리캐스트 콘크리트 임시통 행판을 인양할 수 있는 인양장치 체결부 등을 들 수 있다. 조사 구간은 하부의 보 구조 위에 프리캐스트 콘크리트 임시 통행판을 배치하였으며 연결부와 인양 장치 체결부를 그라우트로 채우는 방식으로 시공된 것으로 분석되었다. 손상 유형 을 분석한 결과, 차량 통행으로 인해 연결부와 인양장치 체결부의 그라우트 재료가 탈락되어 빈 공간이 보이는 부분이 많았으며 이러한 부분을 아스팔트 혼합물로 충진하여 사용하고 있었다. 또한, 콘크리트 임시통행판에 균열이 발생한 경 우도 조사되었다.

보행자 대기공간의 효과척도와 서비스수준 기준은 도로용량편람(2013)에서 제시되고 있다. 보행자 대기공간은 밀집하여 대기하는 공간으로, 횡단보도 대기공간, 지하철 역사, 대합실, 매표소, 엘리베이터 내 등이 이에 해당한다(도로용량편람, 2013). 효과척도는 점유공간으로 측정되며, 이는 보행자가 차지하는 평균 면적을 의미한다. 그러나 도로용량편람(2013)의 기준은 이전 도로용량편람(2001)과 동일한 수치를 적용하고 있어 현 상황을 반영하지 못하고 있다. 이에 따라 대부분의 분석 지점에서 서비스수준이 A로 산출되는 문제가 발생한다(김응철, 2015). 본 연구의 목적은 보행자 대기공간의 서비스수준을 최신화하는 것이다. 연구 절차는 다음과 같다. 첫째, 인체치수를 활 용하여 보행자 대기공간의 점유공간 면적을 재산정하고자 한다. 둘째, 문헌조사를 통해 서비스수준 등급별 기준을 재산 정하고자 한다. 셋째, 최신화된 서비스수준과 도로용량편람(2013)의 기준을 비교하고자 한다. 마지막으로, 현장조사를 통 해 최신화된 서비스수준의 적용 사례를 제시하고자 한다. 연구 결과, 보행자 대기공간의 점유공간 면적을 재산정하고, 이를 기반으로 서비스수준 등급별 기준을 재산정하였다. 도 로용량편람(2013)의 기준과 최신화된 서비스수준 간 차이를 확인하였다. 비교 결과, 점유공간이 2배 증가한 서비스수준임 을 제시하였다. 최신화된 보행자 대기공간 서비스수준을 이용한 실제 보행환경에 관한 적용 사례를 제시하였다.

늘어나는 교통 수요에 대응하기 위해 지하도로 건설이 추진 중이다. 지하도로 건설 시, 진출입부에서의 차량 간 합류 및 분류로 인해 교통정체 및 안전성 저하에 대한 우려가 제기된다. 교통정체가 빈번히 발생하는 경부고속도로 금토JCT-양재IC 구간에 서울-용인 지 하도로, 양재-한남 지하도로, 양재-고양 지하도로 건설이 예정되었다. 특정 구간에 다수의 지하도로 건설 시, 접속부 배치 및 위치에 따라 이동성 및 안전성이 변화할 것으로 고려된다. 본 연구에서는 서울-용인 지하도로와 양재-한남 지하도로, 양재-고양 지하도로에 대한 접속부 배치 및 위치에 따른 이동성 및 안전성 분석을 통해 교통혼잡 완화 및 교통안전이 증가하는 지하도로 연계 방안 도출하 였다. 본 연구에서는 지하도로 연계 방안별 이동성 및 안전성 분석을 위해 4가지 시나리오 (1안 : 지하도로 미시행, 2안 : 지하도로 미 연계, 3안 : 양재-고양 연계, 4안 : 양재-한남 연계)를 선정하였다. 교통 시뮬레이션을 활용해 지상도로 및 지하도로 네트워크를 구축 하고 지하도로 내 차량 주행행태를 구현하였다. 이동성은 평균 통행속도와 통과교통량비로 분석하였으며, 안전성은 상충률을 통해 분 석하였다. 이동성 분석결과, 지상도로 합류부에서는 시나리오 3안 (양재-고양 연계)이 지하도로에서 합류되는 교통량이 가장 적어 모 든 이동성 평가지표에서 가장 큰 이동성 개선 효과가 나타났다. 그러나, 지하도로 합류부에서는 시나리오 3안에 비해 시나리오 4안 (양재-한남 연계)이 이동성 개선 효과가 큰 것으로 나타났다. 이는 유사 교통량 대비 차로수 증가 및 지상도로 합류부 정체의 영향인 것으로 분석된다. 안전성 분석결과, 지상도로 합류부에서는 시나리오 3안이 안전성이 높았으나 지하도로 합류부에서는 시나리오 4안이 안전성이 더 높은 것으로 나타났다. 본 연구의 결과는 시나리오별 교통혼잡 완화 및 교통안전 증진 효과를 정량화해 지하도로 연계 방안 결정을 위한 예비타당성 조사에 반영하는 자료로 활용할 수 있을 것으로 기대된다.

고속도로 2차 사고는 선행 사고(1차 사고) 또는 전방 고장 차량에 의해 교통흐름이 변화된 상황에서 발생하는 사고로, 이에 대한 효과적인 교통안전 관리전략이 필요하다. 그러나 일반사고에 비해 데이터 표본이 부족하여 신뢰성 있는 대응 전략 수립에 어려움이 있다. 본 연구는 고속도로에서 발생하는 2차 사고의 발생 주요 요인을 식별하고 예측하기 위해 BERT(Bidirectional Encoder Representations from Transformers) 기반 텍스트 분석 모델과 전통적 머신러닝 모델 (XGBoost, RandomForest, CatBoost)을 비교하였다. 교통사고 세부기록, 원클릭 속보자료 등 비정형 텍스트 및 정형 데 이터를 수집하고 1차 사고에 관한 시공간적 동적 변수를 통합하여 인공지능 기반의 사고 예측 프레임워크를 구축하였다. 특히, BERT 기반 모델을 통해 교통사고 문맥 정보를 고려하여 단어 삽입 및 대체 기법에 따른 2차사고 데이터 표본을 보완하였다. 또한, 설명가능한 AI(XAI) 기법을 활용하여 주요 사고 요인의 기여도를 시각적으로 해석하고 사고 예방 및 정책 수립에 필요한 정보를 제공하였다. 연구 결과, 제안된 하이브리드 접근법 기반 연구 프레임워크는 높은 정확도의 2 차 사고 발생 가능성 예측에 효과적이며, 교통사고관리시스템의 신뢰성과 효율성 향상에 핵심적인 기여를 할 것으로 기 대된다.