• Journal of Korean Society of Transportation
• /
• v.23 no.7 s.85
• /
• pp.77-86
• /
• 2005

Level of service(LOS) is a quantify measure describing operational conditions within a traffic stream, generally, in terms of such service measures as speed, travel time, freedom to measures, traffic interruptions, comfort and convenience. The LOS is leveled by highway facilities according to measure of effectiveness(MOE) and then used to evaluate performance capacity. The current evaluation of a urban road is performed by only a aspect of traffic operation without any concepts of safety. Therefore, this paper presents a method for evaluation of risk order for urban road with new MOE, user cost analysis, considering both smooth traffic operation(congestion) and traffic safety(accident). The user coat is included traffic accident cast by traffic safety and traffic congestion cost by traffic operation. First of all, a number of traffic accident and accident rate by highway geometric is inferred from urban road traffic accident prediction model (Poul Greibe(2001)) Secondly, a user cost is inferred as traffic accident cast and traffic congestion cost is putting together. Thirdly, a method for evaluation of a urban road is inferred by user cost analysis. Fourthly a accident rate by segment predict with traffic accidents and data related to the accidents in $1996{\sim}1998$ on 11 urban road segments, Gwang-Ju, predicted accident rate. Traffic accident cost predict using predicted accident rate, and, traffic congestion cost predict using predicted average traffic speed(KHCM). Fifthly, a risk order are presented by predicted user cost at each segment in urban roads. Finally, it si compared and evaluated that LOS of 11 urban road segments, Gwang-Ju, by only a aspect of traffic operation without any concepts of safety and risk order by a method for evaluation of urban road in this paper.

• International Journal of Highway Engineering
• /
• v.20 no.2
• /
• pp.119-126
• /
• 2018

PURPOSES : The purpose of this study is to develop a crash prediction model at signalized intersections, which can capture the randomness and uncertainty of traffic accident forecasting in order to provide more precise results. METHODS : The authors propose a random parameter (RP) approach to overcome the limitation of the Count model that cannot consider the heterogeneity of the assigned locations or road sections. For the model's development, 55 intersections located in the Daejeon metropolitan area were selected as the scope of the study, and panel data such as the number of crashes, traffic volume, and intersection geometry at each intersection were collected for the analysis. RESULTS : Based on the results of the RP negative binomial crash prediction model developed in this study, it was found that the independent variables such as the log form of average annual traffic volume, presence or absence of left-turn lanes on major roads, presence or absence of right-turn lanes on minor roads, and the number of crosswalks were statistically significant random parameters, and this showed that the variables have a heterogeneous influence on individual intersections. CONCLUSIONS : It was found that the RP model had a better fit to the data than the fixed parameters (FP) model since the RP model reflects the heterogeneity of the individual observations and captures the inconsistent and biased effects.

• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.12
• /
• pp.55-63
• /
• 2003

The traffic accident is the prerequisite of the traffic accident reconstruction. In this study, the traffic accident (forward collision) and traffic accident reconstruction (inverse collision) simulations are conducted to improve the quality and accuracy of the traffic accident reconstruction. The vehicle and tire models are used to simulate the trajectories for the post-impact motion of the vehicles after collision. The impact dynamic model applicable to the forward and inverse collision simulations is also provided. The accuracy of impact analysis for the vehicular collision depends on the accuracy of the coefficients of restitution and friction. The neural network is used to estimate these coefficients. The forward and inverse collision simulations for the multi-collisions are conducted. The new method fur the accident reconstruction is proposed to calculate the pre-impact velocities of the vehicles without using the trial and error process which requires the repeated calculations of the initial velocities until the forward collision simulation satisfies with the accident evidences. This method estimates the pre-impact velocities of the vehicles by analyzing the trajectories of the vehicles. The vehicle slides on a road surface not only under the skidding during an emergency braking but also under the steering. A vehicle over steering or cornering with excessive speed loses the traction and leaves tile yaw marks on the road surface. The new critical speed formula based on the vehicle dynamics is proposed to analyze the yaw marks and shows smaller errors than ones of the existing critical speed formula.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.13 no.6
• /
• pp.54-63
• /
• 2014

Traffic accident frequency and severity level in Korea are known to be very serious. Especially the number of pedestrian fatalities was much worse and 1.6 time higher than the OECD average. According to the National Police Agency, the flash signals are reported to have many safety benefits as well as travel time reduction, which is opposed to the foreign studies. With this background of expanding the flash signal, this research aims to investigate the overall impact of the flash signal operation on safety, investigating and comparing the accident occurrence on the flash signal and the full signal intersections. For doing this accident prediction models for both flash and full signal intersections were estimated using independent variables (geometric features and traffic volume) and 3-year (2011-2013) accident data collected in Seoul. Considering the rare and random nature of accident occurrence and overdispersion (variance > mean) of the data, the negative binomial regression model was applied. As a result, installing wider crosswalk and increasing the number of pedestrian push buttons seemed to increase the safety of the flash signal intersections. In addition, the result showed that the average accident occurrence at the flash signal intersections was higher than at the full signal-operated intersections, 9% higher with everything else the same.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.28 no.5
• /
• pp.780-790
• /
• 2022

Quantitative risk levels must be presented by analyzing the causes and consequences of accidents and predicting the occurrence patterns of the accidents. For the analysis of marine accidents related to vessel traffic, research on the traffic such as collision risk analysis and navigational path finding has been mainly conducted. The analysis of the occurrence pattern of marine accidents has been presented according to the traditional statistical analysis. This study intends to present a marine accident prediction model using the statistics on marine accidents related to vessel traffic. Statistical data from 1998 to 2021, which can be accumulated by month and hourly data among the Korean domestic marine accidents, were converted into structured time series data. The predictive model was built using a long short-term memory network, which is a representative artificial intelligence model. As a result of verifying the performance of the proposed model through the validation data, the RMSEs were noted to be 52.5471 and 126.5893 in the initial neural network model, and as a result of the updated model with observed datasets, the RMSEs were improved to 31.3680 and 36.3967, respectively. Based on the proposed model, the occurrence pattern of marine accidents could be predicted by learning the features of various marine accidents. In further research, a quantitative presentation of the risk of marine accidents and the development of region-based hazard maps are required.

• Journal of the Korean Society of Safety
• /
• v.34 no.5
• /
• pp.144-152
• /
• 2019

According to the National Police Agency, point-to-point speed enforcement system is being installed and operated in 97 sections across the country. It is more effective than other enforcement systems in terms of stabilizing the traffic flow and inhibiting the kangaroo effect. But it is only 5.1% of the total enforcement systems. The National Police Agency is also aware that its operation ratio is very low and it is necessary to expand point-to-point speed enforcement system. Hence, this study aims to provide the expansion basis of the point-to-point speed enforcement operation through analysis of the quantitative effects and development the accident prediction model. Firstly, this study analyzed the effectiveness of point-to-point speed enforcement system. Naive before-after study and comparison group method(C-G Method) were used as methodologies of analyzing the effectiveness. The result of using the naive before-after study was significant. Total accidents, EPDOs and casualty crashes decreased by 42.15%, 70.64% and 45.30% respectively. And average speed and the ratio of exceeding speed limit decreased by 6.92% and 20.50%p respectively. Moreover, using the C-G method total accidents, EPDOs and casualty crashes decreased by 31.35%, 66.62% and 10.04% respectively. And average speed and the ratio of exceeding speed limit decreased by 3.49% and 56.65%p respectively. Secondly, this study developed a prediction model for the probability of casualty crash. It was dependant on factors of traffic volume, ratio of exceeding speed limit, ratio of heavy vehicle, ratio of curve section, and presence of point-to-point speed enforcement. Finally, this study selected the most danger sections to the major highway and evaluated proper installation sections to the recent installation section by applying the accident prediction model. The results of this study are expected to be useful in establishing the installation standards for the point-to-point speed enforcement system.

• Journal of the Korean Society of Safety
• /
• v.32 no.6
• /
• pp.131-136
• /
• 2017

This study deals with the small-size roundabout accidents. The purpose of this study is to analyze the characteristics of small-size roundabout accidents from developing various types of accident models, and to discuss the improvement countermeasures by vehicle type. The geometric characteristics of 36 roundabouts are surveyed, and the traffic accident data from 2008 to 2014 are collected and classified as those of car, truck and motor cycle. In this study, dependent variable is the number of accident and independent variables are such 15 variables as geometry and traffic volume. The main results are as follows. First, the null hypotheses that the size of roundabout and type of vehicle are not related to traffic accident are rejected. Second, 8 count data models which are all statistically significant are developed. Third, the number of circulatory roadway lane and sidewalk are selected as common variables of roundabout size. Finally, the number of entry and circulatory roadway lane are selected as common variables of vehicle type.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.6 no.3
• /
• pp.71-76
• /
• 2007

The fatalities of pedestrian account for about 40.0% of all fatalities in Korea 2005. Vehicle-Pedestrian accident generates trajectory of pedestrian. In pedestrian involved accident, the most important data to inspect accident is throw distance of pedestrian. The throw distance of pedestrian can be influenced by many variables. The variables that influence trajectory of pedestrian can be classified into vehicular factors, pedestrian factors, and road factors. Vehicular factors are the frontal shape of vehicle, impact speed of vehicle, the offset of impact point. Many studies have been done about the relation between impact speed and throw distance of pedestrian. But the influence of the offset of impact point was neglected. The influence of the offset of impact point was analyzed by Working Model, and the trajectory of pedestrian, dynamic characteristics of multi-body were analyzed by PC-CRASH, a kinetic analysis program for a traffic accident. Based on the results, the increase of offset reduced the throw distance of pedestrian. However box type vehicle just like bus, the offset of impact point did not influence the throw distance of pedestrian considerably.

• Safety and Health at Work
• /
• v.8 no.3
• /
• pp.267-275
• /
• 2017

Background: The mining industry is known worldwide for its highly risky and hazardous working environment. Technological advancement in ore extraction techniques for proliferation of production levels has caused further concern for safety in this industry. Research so far in the area of safety has revealed that the majority of incidents in hazardous industry take place because of human error, the control of which would enhance safety levels in working sites to a considerable extent. Methods: The present work focuses upon the analysis of human factors such as unsafe acts, preconditions for unsafe acts, unsafe leadership, and organizational influences. A modified human factor analysis and classification system (HFACS) was adopted and an accident predictive fuzzy reasoning approach (FRA)-based system was developed to predict the likelihood of accidents for manganese mines in India, using analysis of factors such as age, experience of worker, shift of work, etc. Results: The outcome of the analysis indicated that skill-based errors are most critical and require immediate attention for mitigation. The FRA-based accident prediction system developed gives an outcome as an indicative risk score associated with the identified accident-prone situation, based upon which a suitable plan for mitigation can be developed. Conclusion: Unsafe acts of the worker are the most critical human factors identified to be controlled on priority basis. A significant association of factors (namely age, experience of the worker, and shift of work) with unsafe acts performed by the operator is identified based upon which the FRA-based accident prediction model is proposed.

• Journal of the Korean Institute of Gas
• /
• v.24 no.5
• /
• pp.47-55
• /
• 2020

Hazardous materials accidents are not limited to the leakage of the material, but if the early response is not appropriate, it can lead to a fire or an explosion, which increases the scale of the damage. However, as the 4th industrial revolution and the rise of the big data era are being discussed, systematic analysis of hazardous materials accidents based on new techniques has not been attempted, but simple statistics are being collected. In this study, we perform the systematic analysis, using machine learning, on the fire accident data for the past 11 years (2008 ~ 2018), accumulated by the National Fire Service. The analysis results are visualized and presented through text mining analysis, and the possibility of developing a damage-scale prediction model is explored by applying the regression analysis method, using the main factors present in the hazardous materials fire accident data.