• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.273-279
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• 2022

Owing to the need to establish a cooperative-intelligent transport system (C-ITS) environment in the transportation sector locally and abroad, various research and development efforts such as high-tech road infrastructure, connection technology between road components, and traffic information systems are currently underway. However, the current central control center-oriented information collection and provision service structure and the insufficient road infrastructure limit the realization of the C-ITS, which requires a diversity of traffic information, real-time data, advanced traffic safety management, and transportation convenience services. In this study, a network construction method based on the existing received signal strength indicator (RSSI) selected as a comparison target, and the experimental target and the proposed intelligent edge network compared and analyzed. The result of the analysis showed that the data transmission rate in the intelligent edge network was 97.48%, the data transmission time was 215 ms, and the recovery time of network failure was 49,983 ms.

• Proceedings of the KAIS Fall Conference
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• 2008.05a
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• pp.248-250
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• 2008

This paper proposes a prediction method to prevent traffic accident and reduce to vehicle waiting time using neural network. Computer simulation results proved reducing average vehicle waiting time which proposed coordinating green time better than electro-sensitive traffic light system dose not consider coordinating green time. Moreover, we present neural network approach for traffic accident prediction with unnormalized (actual or original collected) data. This approach is not consider the maximum value of data and possible use the network without normalizing but the predictive accuracy is better. Also, the unnormalized method shows better predictive accuracy than the normalized method given by maximum value. Therefore, we can make the best use of this model in software reliability prediction using unnormalized data. Computer simulation results proved reducing traffic accident waiting time which proposed neural network better than conventional system dosen't consider neural network.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.160-173
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• 2021

Recently, research on the development of autonomous vehicles has increased worldwide. Moreover, a means to identify and analyze the characteristics of traffic accidents of autonomous vehicles is needed. Accordingly, traffic accident data of autonomous vehicles are being collected in California, USA. This research examined the characteristics of traffic accidents of autonomous vehicles. Primarily, traffic accident data for autonomous vehicles were analyzed, and the text data used text-embedding techniques to derive major keywords and four topics. The methodology of this study is expected to be used in the analysis of traffic accidents in autonomous vehicles.

• International Journal of Highway Engineering
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• v.16 no.4
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• pp.111-118
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• 2014

PURPOSES: The purposes are to analyze the pedestrian accident severity and to develop the accident models by arterial road function. METHODS: To analyze the accident, count data and ordered logit models are utilized in this study. In pursuing the above, this study uses pedestrian accident data from 2007 to 2011 in Cheongju. RESULTS : The main results are as follows. First, daytime, Tue.Wed.Thu., over-speeding, male pedestrian over 65 old are selected as the independent variables to increase pedestrian accident severity. Second, as the accident models of main and minor arterial roads, the negative binomial models are developed, which are analyzed to be statistically significant. Third, such the main variables related to pedestrian accidents as traffic and pedestrian volume, road width, number of exit/entry are adopted in the models. Finally, Such the policy guidelines as the installation of pedestrian fence, speed hump and crosswalks with pedestrian refuge area, designated pedestrian zone, and others are suggested for accident reduction. CONCLUSIONS: This study analyzed the pedestrian accident severity, and developed the negative binomial accident models. The results of this study expected to give some implications to the pedestrian safety improvement in Cheongju.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.31-40
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• 2011

Generally, inappropriate driving conditions including geometric, traffic environmental, and driver psychological problems may be critical reasons of traffic accidents. Under this circumstance, various types of facilities have been installed to improve traffic safety by itself or as a set consisting of several other traffic safety facilities. In general, traffic accidents occur by several reasons combined rather than only a single reason, and thus the safety effect of the safety facilities cannot be simply analyzed with only a single improvement. For the study, traffic accident data on the roadway segments of interest are collected along with field survey data. For the analysis, various alternative analysis methods were evaluated in terms of assessing accident reduction from various types of traffic safety improvements. Among the alternative methods tested including simple before-and-after evaluation method, before-and-after evaluation yoked comparison, and Comparison Group (C-G) method, it was found that the C-G method is the most effective method for analyzing the traffic safety improvement effect. Adopting the C-G method, both single and multiple safety improvements were analyzed. The results from this study can potentially be applied to decide the best type of treatments to improve traffic safety as well as to measure the accident reduction effects from the treatments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.29-38
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• 2018

This study aims to propose a method for the estimation of operational delay cost using transportation card data in bus accidents. Average operational delay time from bus accidents was surveyed among 12 bus companies through an interview method. Then, the operational delay cost was estimated using actual traffic accident data and transportation card data. Results showed that average loss time per bus accident was found to be 45 minutes. In addition, total occupancy of 659 was estimated for the accidents investigated using transportation card data, resulting a total loss time of 494.25 hours. An estimated operational delay cost was 186.9 thousand won per accident, which was 6.37% of social agency cost. The magnitude of this number implied that operational delay cost may have a significant impact on traffic accident cost if included.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.4
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• pp.921-929
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• 2015

Road conditions which obstruct the driver from seeing road markings, such as in the evening or in the rain, due to the lack of a light source gives way to increasing the risk of traffic accidents. In order to increase road safety, the Korea Expressway Corporation set up a pilot project which used high-quality materials along a section of the Gyeongbu Expressway between Daejeon and Pangyo. There is little research on high-quality materials in the field of pavement marking. This study introduces high-quality materials used in pavement materials, presents the results of a survey conducted to examine the effect of the pilot project and analyzes traffic accident data from before and after the implementation of the pilot project. The survey results show that 87% of the respondents were highly satisfied with the pilot project. With the goal of evaluating the effect of the pilot project, this study used traffic accident data provided by the Korea Expressway Corporation accident data and performed a before-after study of the number of traffic. The results of data analysis show that there were 62 and 48 traffic accidents before and after the implementation of the pilot project. In addition, the result of Emperical Bayes Method indicates that there is an 41.7% decrease in the number of traffic accidents as an effect of High-quality Pavement Marking Materials.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.1
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• pp.49-56
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• 2021

The purpose of this study is to develop a methodology to select a cluster of night traffic accidents using CRP (Continuous Risk Profile) analysis. the other purpose of this study is to present the characteristics of the traffic accident cluster section selected at night using CRP analysis. The CRP analysis was performed considering traffic volume of target routes through traffic accident data. In addition, variables were set according to the freeway sections. the method of subtracting the daytime CRP from the nighttime CRP was used to analyze the nighttime traffic accident. As a result, Using the CRP analysis, the sections of hotspot were identified and plotted based on traffic accidents. Also, the sections where traffic accidents are frequent were those where IC or Tunnels were installed, and there was a deviation from the general section. In conclusion, CRP analysis could be used to calculate the frequent section of specialized traffic accidents at night, and it was selected as a point in need of improvement due to the frequent occurrence of specialized traffic accidents at night in the section where IC or tunnel facilities are installed. In addition, it is inferred that the number of specialized traffic accidents at night in the section where IC or tunnel facilities are installed is a factor in the problem of night visibility due to lighting facilities.

• Sleep Medicine and Psychophysiology
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• v.8 no.1
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• pp.45-51
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• 2001

Objectives: The experience of traffic accident is a kind of the psychosocial stressors to person. The traffic accident-related patients may show the psychophysiologic hyperarousal. So we examined the differences of psychophysiologic response between patients with and without the memory of experienceing a traffic accident. Methods: Twenty-four traffic accident-related patients were divided into two groups according to ther memory of a traffic accident. In psychological assessment, levels of anxiety and depression were evaluated by State-Trait Anxiety Inventory, Beck's Depression Inventory, and Hamilton Rating Scales For Anxiety and Depression. Heart rate, electrodermal response (EDR), and electromyographic activity (EMG) were measured by biofeedback system, and systolic and diastolic blood pressure by automated vital sign monitor during baseline, task, and rest periods. We utilized script-driven imagery technique as a stressful task. The patients listened to the script describing their own traffic accident experience and were instructed to imagine the event during the task period. Statistically analytic data were obtained from the differences of psychological and psychophysiologic data between two groups. Results: The memory group did not show significantly higher EDR than the none memory group, but showed higher tendency during baseline, imagery, and rest periods. The memory group showed significantly lower EMG than the none memory group during rest period. However, there were no differences in other psychophysiologic reponses between the two groups. Conclusion: Our results showed that the memory group had higher tendency in autonomic arousal level such as electrodermal response than the none memory group. We suggest that physicians need to minimize repetitive imagery of traffic accident (reexperience), and decrease the autonomic hyperarousal in the treatment of traffic accident-related patients.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.119-129
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• 2014

This study aims to evaluate the accident reduction effects of 'Section Speed Enforcement System' (SSES) operation in freeways. In pursuing the above, this study collects the accident data for 5 years (2 years before operation and 3 years after operation) at all 9 sections where SSESs are operated, and evaluates annually the effects before and after operation using the comparison group method (C.G. Method). The measures of effectiveness are total accidents (TAs), fatal and serious accidents (FSAs), total injuries (TIs) and fatal and serious injuries (FSIs). The main results are as follows. First, TAs and TIs are reduced to 41.7 and 17.1%, respectively. Second, FSAs and FSIs are reduced to 41.7 and 32.2%, respectively. Therefore, SSES has more effectiveness at fatal and serious accident. Third, the accident reduction effect has been increasing, and particularly the effect of 'after three years' is evaluated to be notable.