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.

Autonomous vehicle technology is targeted for commercialization in 2027. However, a mixed traffic environment of conventional vehicles and autonomous vehicles is expected to be inevitable. In mixed traffic, conventional vehicles drive at reduced speeds due to limited visibility, while autonomous vehicles can drive at normal speeds using sensors. The difference in driving speeds between the two vehicles creates a mismatch in traffic flow, and the risk of congestion and accidents is likely to increase. It is necessary to analyze the impact of the interaction between autonomous vehicles and regular vehicles on traffic safety in advance and develop management measures to mitigate it. In this study, we aim to analyze the effect of reducing the speed deviation between general vehicles and autonomous vehicles by providing the driving speed deceleration level information to autonomous vehicles in the event of fog to induce the same traffic flow and improve the safety level accordingly. We examined the method of delivering the driving speed deceleration level information to autonomous vehicles. When providing speed limit information to autonomous vehicles through systems such as VMS, each country has different ways of recognizing regulatory symbols. Due to these differences, it may not be easy to provide regulatory information to overseas vehicles through external systems such as VMS in Korea. For this reason, there is a possibility that autonomous vehicles may violate laws and regulations by not recognizing them properly, and there are still limitations in defining the responsibility for applying laws and regulations between countries. Therefore, we adopted an information provision approach that encourages autonomous vehicles to maintain a harmonious traffic flow with regular vehicles by sharing safe driving speed information to be encouraged at the public center level. To analyze the effectiveness of these safe driving speed management measures, we used a quantitative indicator, the number of observable conflicts, to distinguish the mixing ratio of regular vehicles and autonomous vehicles. The analysis was divided into early (30%), mid (50%), and late (80%) periods of autonomous vehicle introduction. As a result of giving autonomous vehicles the same traffic flow as regular vehicles, the number of collisions decreased by 128 collisions/hour in the early period, 393 collisions/hour in the mid period, and 337 collisions/hour in the late period. This indicates that the interaction between autonomous vehicles and conventional vehicles becomes more complex as the mixing ratio increases, and the effectiveness of the safe speed management measures proposed in this study increases accordingly. These results can be used as an important basis for transportation policy and design.

As the transportation paradigm shifts from vehicle-oriented to pedestrian-oriented, active research has been conducted on road designs that consider the safety of pedestrians, cyclists, and personal mobility users. This study aims to respond to this change by developing installation warrant factors and improving the minimum size design standards for triangular islands. This study involved reviewing domestic and international laws and guidelines, analyzing the current installation status of triangular islands, examining case studies of improvements, and assessing policy changes. Based on the findings, important insights were derived, and improvement plans to enhance the safety of pedestrians, vulnerable users, and other road users were proposed. This study identified several issues and confirmed that policies in both domestic and international contexts are shifting towards minimizing or removing the triangular islands. Based on these findings, this study developed 24 factors for installation warrants to determine the installation of triangular islands, such as the design speed and peak-hour volume for pedestrians. In addition, the proposed improvements suggest increasing the minimum size design standards from 9m2 to 22m2 to ensure the safety of users. The factors of installation warrants and improved minimum size design standards proposed in this study are expected to help shift the operation of triangular islands from a vehicle-oriented to a pedestrian-oriented approach.

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.