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 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.

국내에서 겨울철 발생하는 결빙사고는 전체적인 교통사고 대비 치사율이 1.7배 높은 것으로 나타났다. 주행속도가 높은 고속국도의 경우 결빙사고 치사율은 18.7로, 결빙 외 고속국도 교통사고 치사율인 4.2와 비교하여 약 4.5배 높았다(KoROAD, 2024). 특히 교량과 터널과 같은 도로시설물은 구조적 특성과 환경적 요인으로 인해 결빙 형성에 매우 취약하다. 교량은 지면으로부터의 열전달이 차단되 기 때문에 겨울철 노면온도가 낮아 결빙이 형성될 가능성이 높으며, 터널은 겨울철 낮은 온도와 터널 입출구부의 응달지역 형성 및 터널 내부와 외부 공기로 인한 급격한 온도변화로 인해 결빙이 발생할 가능성이 높다. 또한, 도로시설물은 교통사고 발생 시 치사율이 높게 나타나는 경향이 있다. 실제로 교량과 터널에서 발생한 교통사고의 치사율은 전체 1.94, 터널 5.05, 교량 4.10으로 도로시설물에서 발생한 교통사고의 치사율이 높았다(KoROAD and ACCRC, 2017). 따라서 도로시설물에서 발생하는 결빙사고는 쉽게 결빙이 형성되 는 환경조건과 사고 발생 시 치사율이 높은 특성으로 인해 일반 도로보다 높은 위험성을 내포하고 있다. 그러나 현재로써 도로시설물 에서 발생하는 결빙사고의 원인과 위험성을 중점적으로 분석한 연구는 그 수가 부족하며, 기존 연구들은 결빙 구간의 기후적 특성이 나 개별 결빙사고 사례 분석에 국한되어 있어 도로시설물은 결빙사고 분석 시 여러 가지 환경요인 중 하나로서만 고려되고 있는 실정 이다. 본 연구에서는 도로시설물에서의 결빙사고 위험도를 평가하는 방법을 제시하고, 이를 Min-Max(최소-최대) 정규화 과정을 통해 구체 화함으로써 보다 체계적인 분석이 가능하도록 한다. 이를 통해 도로시설물의 겨울철 운영에 있어 효과적인 결빙사고 방지 대책을 수 립하는 데 기여하고자 한다.

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 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 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 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.

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.

PURPOSES : This study aimed to derive the factors that contribute to crash severity in mixed traffic situations and suggest policy implications for enhancing traffic safety related to these contributing factors. METHODS : California autonomous vehicle (AV) accident reports and Google Maps based on accident location were used to identify potential accident severity-contributing factors. A decision tree analysis was adopted to derive the crash severity analyses. The 24 candidate variables that affected crash severity were used as the decision tree input variables, with the output being the crash severity categorized as high, medium, and low. RESULTS : The crash severity contributing factor results showed that the number of lanes, speed limit, bus stop, AV traveling straight, AV turning left, rightmost dedicated lane, and nighttime conditions are variables that affect crash severity. In particular, the speed limit was found to be a factor that caused serious crashes, suggesting that the AV driving speed is closely related to crash severity. Therefore, a speed management strategy for mixed traffic situations is proposed to decrease crash severity and enhance traffic safety. CONCLUSIONS : This paper presents policy implications for reducing accidents caused by autonomous and manual vehicle interactions in terms of engineering, education, enforcement, and governance. The findings of this study are expected to serve as a basis for preparing preventive measures against AV-related accidents.

2020년 국토교통부에서는 ‘결빙 취약구간 평가 세부 배점표’에 의하면, 전국의 고속국도 및 일반국도를 대상으로 결빙 취약 구간 464 개소를 선정하여 관리중에 있다. 그러나 감사원은 2020년 진행한 주요 사회기반시설(도로ㆍ고속철도) 안전관리실태 감사에서 결빙 취 약 구간 선정 시 터널 입출구부 등 결빙위험이 큰 구간이 도로포장 홈파기 대상구간에서 누락된 점을 지적하였다. 이러한 근거로 결 빙에 취약한 터널 입ㆍ출구에서 결빙사고가 우려되는 등 ‘겨울철 도로교통 안전 강화대책’의 실효성이 저하될 가능성이 제시되었다. 또한 본 연구에서 자체적으로 검토한 결과, 4개 특성 12개 항목으로 구성된 ‘결빙 취약구간 평가 세부 배점표’의 도로시설 항목에서 터널, 교량 등 도로시설물의 배점 부여 기준을 확인하기 어려웠으며, 각 도로시설에 대한 정의가 모호하여 평가표의 현장 적용성이 제 한되거나 신뢰도 검증이 부족한 점을 확인하였다. 본 연구에서는 국토교통부에서 제공하는 노드(Node) 및 링크(Link) 기반의 국내 도로망 GIS(Geographic Information System)데이터 에 결빙사고 데이터의 위치정보를 결합하여 고속국도 및 일반국도의 터널 및 교량 등을 포함하는 도로시설물 및 그 주변에서 발생한 결빙사고 이력을 자료화하였다. 최종적으로 도로시설물별 결빙사고 발생 비율 및 사고 심각도(사망자, 부상자 수)에 대한 분석을 통해 도로시설물의 결빙사고 상관 정도와 영향 범위를 파악하였다.

PURPOSES : This study empirically examines the determinants of traffic accidents by focusing on the transport culture index. METHODS : Two-stage least-squares estimation using an instrumental variable is used as the identification strategy. As the instrumental variable of the transport culture index, its past values, particularly before the outbreak of COVID-19 in 2018 are used. RESULTS : The empirical results, considering the potential endogeneity of the transport culture index, show that areas with higher values of the index are likely to have fewer traffic accident casualties. Local governments of regions with relatively frequent traffic accidents can run campaigns for residents to fasten their seatbelts, causing reverse causation. Ignoring this type of endogeneity underestimates the importance of the index as a key determinant of traffic accidents. CONCLUSIONS : Several traffic accidents occur in Korea, e.g., 203,130 accidents with 291,608 injuries and 5,392 deaths. As traffic accidents cause social costs, such as delays in traffic flow and damage to traffic facilities, public interventions are required to reduce them. However, the first step in public intervention is to accurately understand the relationship between the degree of damage in traffic accidents and the transport-related attributes of the areas where the accidents occurred. Although the transport culture index appears to be an appropriate indicator for predicting local traffic accidents, its limitations as a comprehensive index need to be addressed in the future.

국토교통부는 2020년 '결빙 취약구간 평가 세부 배점표’에 따라, 전국의 고속국도와 일반국도를 대상으로 410개 구간의 결빙 취약구 간을 선정하였다. 그러나, 2021년 감사원의 결빙 취약구간 지정 적정성 감사 결과에서 감사원은 현재 지정ㆍ관리 중인 결빙 취약구간 및 결빙 취약구간 평가 세부 배점표의 적정성에 문제를 제기하였다. 이에, 국토교통부는 결빙 취약구간을 재지정하여 발표하였으나 그 에 대한 평가 및 지정 적정성 검증이 아직 이루어지지 않았다. 본 연구에서는 결빙 취약구간과 결빙사고 데이터의 위치정보를 수집하여 GIS(Geographic Information System) 데이터로 구축하고 맵핑(Mapping)하여 결빙 취약구간 내 결빙사고이력을 확인함으로서 결빙 취약구간의 결빙사고 예측성능을 평가하였다. 또한, 각 결빙 사고 발생지점에서 도로시설, 교통, 선형구조, 환경인자 데이터를 수집하여 분석한다. 이를 통해 결빙사고와 각 인자 간의 상관성을 파 악하고, 그 결과에 따라 결빙 취약구간 평가 세부 배점표의 평가항목 및 각 항목별 배점을 수정하고 보완함으로써 결빙 취약구간의 신뢰성을 제고한다.

겨울철 국내 도로 결빙으로 인한 교통사고가 증가하는 추세를 보이고 있으며 2018년~2022년까지 총 4,609건의 결빙 교통사고가 발 생하였다. 결빙 교통사고의 치사율은 2.3으로 일반적인 교통사고와 비교하여 높은 치사율을 보이며 최근 5년(2018~2022)동안 결빙 교 통사고로 인하여 107명이 사망자와 7,728명의 부상자가 발생하였다. 현재 국토교통부에서 제시한 결빙 취약구간 평가기준표에 따라 결 빙 위험 구간을 지정하고 있으나, 해당 기준은 결빙의 주요 요인으로 고려되는 기상조건을 충분히 반영하지 못하고 있다. 도로 결빙은 노면온도가 0℃ 이하이며 노면에 수분이 공급될 때 형성되며 기온, 구름량, 풍속, 풍향, 상대습도, 강수량 등의 기상인자들이 복합적으 로 작용하여 결빙이 발생한다는 점을 고려하였을 때, 기상 특성은 도로 결빙의 주요 인자로 판단된다. 따라서 국내 결빙 취약구간 평 가기준의 개선이 필요하며 본 연구의 목적은 국내 결빙 교통사고 데이터를 분석하고 결빙이 형성되는 기상 조건을 구체화하는 것이다. 분석을 위한 데이터로 2018년~2022년까지 5년동안 발생한 결빙사고 사례와 기상청 방재기상관측소(AWS)에서 제공하는 기상 데이터 를 적용하였다. 이후, 박스도표, 확률밀도함수 등의 통계분석을 적용하여 결빙 형성 기상 조건을 구체화하였다. 이를 통하여 기존 결빙 취약구간 평가기준의 기상학적 개선 방향성을 제시할 수 있으며 더 나아가 도로 결빙 예측 로직 개발을 기대할 수 있다.

PURPOSES : This study aimed to identify factors affecting the duration of traffic incidents in tunnel sections, as accidents in tunnels tend to cause more congestion than those on main roads. Survival analysis and a Cox proportional hazards model were used to analyze the determinants of incident clearance times. METHODS : Tunnel traffic accidents were categorized into tunnel access sections versus inner tunnel sections according to the point of occurrence. The factors affecting duration were compared between main road and tunnel locations. The Cox model was applied to quantify the effects of various factors on incident duration time by location. RESULTS : Key factors influencing mainline incident duration included collision type, driver behavior and gender, number of vehicles involved, number of accidents, and post-collision vehicle status. In tunnels, the primary factors identified were collision type, driver behavior, single vs multi-vehicle involvement, and vehicles stopping in the tunnel after collisions. Incidents lasted longest when vehicles stopped at tunnel entrances and exits. In addition, we hypothesize that incident duration in tunnels is longer than in main roads due to the reduced space for vehicle handling. CONCLUSIONS : These results can inform the development of future incident management strategies and congestion mitigation for tunnels and underpasses. The Cox model provided new insights into the determinants of incident duration times in constrained tunnel environments compared to open main roads.

PURPOSES : This study aims to analyze the causes of pedestrian traffic accidents on community roads. METHODS : This study collected variables affecting pedestrian traffic accidents on community roads based on field surveys and analyzed them using negative binomial regression and zero-inflated negative binomial regression models. RESULTS : Model analysis results showed that the negative binomial regression model is more suitable than the zero-inflation negative binomial regression model. Additionally, the segment length (m), pedestrian volume (persons/15 min), traffic volume (numbers/15 min.), the extent of illegal parking, pedestrian-vehicle conflict ratio, and one-way traffic (one: residential, two: commercial) were found to influence pedestrian traffic accidents on community roads. Model fitness indicators, comparing actual values with predicted values, showed an MPB of 1.54, MAD of 2.57, and RMSE of 7.03. CONCLUSIONS : This study quantified the factors contributing to pedestrian traffic accidents on community roads by considering both static and dynamic elements. Instead of uniformly implementing measures, such as pedestrian priority zones and facility improvements on community roads, developing diverse strategies that consider various dynamic factors should be considered.

PURPOSES : This study investigates the factors affecting extra-long tunnel accidents by integrating data on tunnel geometry, traffic flow, and traffic accidents and derives the underlying implications to mitigate the severity of accidents. METHODS : Two processes centered on three key data points (tunnel geometry, traffic flow, and traffic accidents) were used in this study. The first is to analyze the spatial characteristics of extra-long tunnel traffic accidents and categorize them from multiple perspectives. The other was to investigate the factors affecting extra-long tunnel traffic accidents using the equivalent property-damage-only (EPDO) of individual accidents and the aforementioned data as the dependent and independent variables, respectively, by employing an ordered logistic regression model. RESULTS : Gyeonggi-do, Gyeongsangnam-do, and Gangwon-do are three metropolitan municipalities that have a significant number of extra-long tunnel accidents; Busan and Seoul have the most extra-long tunnel accidents, accounting for 23.2% (422 accidents) and 18.6% (339 accidents) of the 1,821 accidents that occurred from 2007 to 2020, respectively. In addition, approximately 70% of extra-long tunnel traffic accidents occurred along tunnels with lengths of less than 2 km, and Seoul and Busan accounted for over 60% of the top 20 extra-long tunnels with accidents. Most importantly, the Hwangryeong (down) tunnel in Busan experienced the most extra-long tunnel traffic accidents, with 77 accidents occurring during the same period. As a result of the ordered logistic regression modeling with EPDO and multiple independent variables, the significant factors affecting the severity of extra-long tunnel traffic accidents were determined to be road type (freeway, local route, and metropolitan city road), traffic flow (speed), accident time (year, summer, weekend, and afternoon), accident type (rear end), traffic law violations (safe distance violation and center line violation), and offending vehicles (van, sedan, and truck). CONCLUSIONS : Based on these results, the following measures and implications for mitigating the severity of extra-long tunnel traffic accidents must be considered: upgrading the emergency response level of all road types to that of freeways and actively promoting techniques for regulating high-speed vehicles approaching and traversing within extra-long tunnels are necessary. In addition, the emergency response and preparation system should be reinforced, particularly when the damage from extra-long tunnel traffic accidents is more serious, such as during the summer, weekends, and afternoons. Finally, traffic law violations such as safe distance and centerline violations in extra-long tunnels should be prohibited.

This study aims to understand the current status of exemptions for traffic accidents during the return of emergency vehicles and to provide suggestions for improvement. A survey was conducted on 3,500 firefighters to investigate the perception of traffic accidents during the return of emergency vehicles, and responses from 505 participants were analyzed. Based On the demographic characteristics and perception of the participants, frequency analysis and variance analysis were used as research methods to analyze basic statistics and the current situation. The results showed that firefighters have concerns and anxieties about traffic accidents during the return of emergency vehicles, and the need for applying exemptions and enacting explicit legal provisions was statistically confirmed. Based on these results, we suggest a policy for exemptions to improve the preparation for re-deployment and to alleviate the concerns and anxieties of firefighters.