• Title/Summary/Keyword: traffic accident data

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Crash Characteristics within the Bridge Influence Area of Expressway Using the Discriminant Analysis (판별분석을 이용한 고속도로 교량영향권역 교통사고 특성분석에 관한 연구)

  • Park, JeJin
    • International Journal of Highway Engineering
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    • v.16 no.6
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    • pp.149-158
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    • 2014
  • PURPOSES : The bridge section of the expressway has a worse driving environment than the general section. However, traffic safety countermeasures are focused only on the bridge section. Traffic safety countermeasures on the section before entry to the bridge and the section after exit from the bridge are applied only when the bridge has a long-span section. Accordingly, this study will verify the necessity of extending the application of traffic safety countermeasures to areas that are affected by the bridge. METHODS : This study determines the areas that are affected by the bridge as well as the areas that are affected by locations with frequent traffic accidents and suggests the risk factors by affected areas through canonical discriminant analysis. For the analysis, traffic accident data for 3 years, which occurred on bridge sections in six major expressway lines, were used. RESULTS : The numbers of traffic accidents were 469 before the bridge, 281 on the bridge, and 468 after the bridge. The variables that have impact on the seriousness of accidents are as follows: speeding, excess manipulation of the steering wheel, and failure to secure safety distance for accidents that occurred before the bridge section; speeding, excess manipulation of the steering wheel, and dozing off for accidents that occurred on the bridge; and speeding and failure to secure safety distance for accidents that occurred after the bridge section. CONCLUSIONS : Areas affected by the bridge show higher accident rates than the bridge section; therefore, imposing traffic safety countermeasures on the integrated section of the bridge and the affected areas is required. It is believed that the results suggested in this study could be effectively used in the prevention of traffic accidents by imposing custom-made safety countermeasures for each section.

Developing the Traffic Accident Models of Arterial Link Sections by Driving Type (운전 유형에 따른 가로구간 사고모형 개발)

  • Kim, Kyung-Hwan;Park, Byung-Ho
    • Journal of the Korean Society of Safety
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    • v.25 no.6
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    • pp.197-202
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    • 2010
  • This study deals with the accident models of arterial link sections by driving type. The objectives is to develop models by driving type using the accident data of 24 arterial links in Cheong-ju. In pursuing the above, this study gives particular emphasis to modeling such the accidents as the straight, lane change and others. The main results analyzed are as follows. First, the number of accidents is analyzed to account for about 59% in straight, 31% in lane change and 10% in others. Second, the number of left-turn lane as common variables, and the ADT, number of pedestrian crossings, connecting roads and link length as specific variables are selected in developing models(number of accident and EPDO). Third, 8 models which are all statistically significant are developed. Finally, RMSE of the driving type models was analyzed to be better than that of dummy variable.

Recognition of Dangerous Driving Using Automobile Black Boxes (차량용 블랙박스를 활용한 위험 운전 인지)

  • Han, In-Hwan;Yang, Gyeong-Su
    • Journal of Korean Society of Transportation
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    • v.25 no.5
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    • pp.149-160
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    • 2007
  • Automobile black boxes store and provide accident and driving information. The accident and driving information can be utilized to build scientific traffic-event database and can be applied in various industries. The objective of this study is to develop a recognition system of dangerous driving through analyzing the driving characteristic patterns. In this paper, possible dangerous driving models are classified into four models on the basis of vehicle behaviors(acceleration, deceleration, rotation) and accident types from existing statistical data. Dangerous driving data have been acquired through vehicle tests using automobile black boxes. Characteristics of driving patterns have been analyzed in order to classify dangerous driving models. For the recognition of dangerous driving, this study selected critical value of each dangerous driving model and developed the recognition algorithm of dangerous driving. The study has been verified by the application of recognition algorithm of dangerous driving and vehicle tests using automobile black boxes. The presented recognition methods of dangerous driving can be used for on-line/off-line management of drivers and vehicles.

Development of Traffic Accident Rate to Improve the Reliability of the Valuation of Accident Costs Savings on National Highways (국도 사고비용 산정의 신뢰도 향상을 위한 사고원단위 개선)

  • Wanhyoung Cho;Kijung Kum
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.5
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    • pp.19-29
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    • 2023
  • The accident rate in South Korea is simply classified according to the road type and the number of lanes, but other countries apply various factors affect accidents. In this study, national highways where accidents occurred were divided into urban, rural, older, and modern roads using TAAS(Traffic Accident Analysis System) data, and a model of accident costs savings is suggested. As a result of analyzing 1,416.2 km, the fatality rate(person/100mil-vehicle·km) was 4.21 for urban-older, 1.37 for urban-modern, 2.18 for rural-older, and 0.99 for rural-modern roads. The rates of urban roads had a higher result than rural. The injury rate(person/100mil-vehicle·km) for urban-older was 182.63, that for urban-modern was 103.42, that for rural-older was 67.44, and that for rural-modern road was 42.96, which showed a similar pattern to fatality rates. Accident rates of a modern road were much lower than the KDI Guideline. The benefit of applying the result of this study was calculated and the valuation of accident costs savings is increased from 0.6% to 14.1%, while B/C is improved from 0.626 to 0.724.

Analysis of the Effect of Traffic Safety Investment on Traffic Accident Reduction Using Panel Data (패널자료를 이용한 교통안전투자 종류별 사고감소 효과)

  • Gang, Su-Cheol;Bae, Hyeong
    • Journal of Korean Society of Transportation
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    • v.29 no.5
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    • pp.19-32
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    • 2011
  • There are many investment budget drafts in the filed of a road traffic safety. The traffic safety budget is spitted into following three major areas: 1) traffic safety facility (Engineering), 2) traffic enforcement (Enforcement), and 3) traffic safety education & public relation (Education). The three area are known as so-called 3E policy. This study investigates the effect of the investment in the 3E policy on the reduction of traffic accidents analyzing the data annually collected from the 15 local governments during 1992 to 2007. The analysis employing the traffic accidents as the dependent variable reveals that the effect of the investment is higher if same amount of investment is made on areas of the traffic safety education and public relation than the area of facility improvement. The similar conclusions are resulted from the separate investigation of traffic accidents data by 6 different types. All the results consistently indicate that the current traffic safety investment being primarily made on traffic safety facility needs to shift to the areas of traffic safety education and public relation budget.

Performance Comparison of Machine-learning Models for Analyzing Weather and Traffic Accident Correlations

  • Li Zi Xuan;Hyunho Yang
    • Journal of information and communication convergence engineering
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    • v.21 no.3
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    • pp.225-232
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    • 2023
  • Owing to advancements in intelligent transportation systems (ITS) and artificial-intelligence technologies, various machine-learning models can be employed to simulate and predict the number of traffic accidents under different weather conditions. Furthermore, we can analyze the relationship between weather and traffic accidents, allowing us to assess whether the current weather conditions are suitable for travel, which can significantly reduce the risk of traffic accidents. In this study, we analyzed 30000 traffic flow data points collected by traffic cameras at nearby intersections in Washington, D.C., USA from October 2012 to May 2017, using Pearson's heat map. We then predicted, analyzed, and compared the performance of the correlation between continuous features by applying several machine-learning algorithms commonly used in ITS, including random forest, decision tree, gradient-boosting regression, and support vector regression. The experimental results indicated that the gradient-boosting regression machine-learning model had the best performance.

An Economic Approach for Improvement of Radius for Hazarouds Road (위험도로 곡선반경 개선의 경제적 접근에 관한 연구)

  • Ha, Tae-Jun;Kim, Jeong-Hyun;Yoon, Pan;Park, Je-Jin;Kim, Young-Woon
    • Journal of Korean Society of Transportation
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    • v.21 no.5
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    • pp.73-81
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    • 2003
  • The Government presented improvement plans such as "Traffic Accident Frequent Point" and "Hazardous Roads" to reduce traffic accidents on the increase after 1980s. In case of the hazardous roads, they are expressed by grades which are marked by geometric elements such as width, radius, grade. sight distance. and other environmental factors. As each business for improving roads goes by only focusing on improvement of geometric elements, excessive expense can be invested too much nowadays causing economical waste. Therefore, as improvement plans approached by economic access are needed, this paper shows the cost-effective improvement of the business to keep safety related to traffic accident and economical waste. The hazardous roads which authorized by Gwang-ju National Road Preservation Office of Construction and Transportation Ministry in 1995 for business for improvement of roads, were investigated before 1999. First of all, estimating traffic accident models are presented by using existed data statistically. The models help to maximize traffic accident decrease through control of the presented factor. Secondly, optimum construction cost of improvement is presented to prevent overcapitalization. However, this paper is limited because it was difficult to sort the data with various areas and to approach various ways.

A Study on the Safety of Passing-type Climbing Lanes in Expressways using C-G Method (비교그룹방법을 이용한 고속도로 추월차로형 오르막차로 안전성 연구)

  • Kim, Bong Soo;Kim, Sang-Gu;Yun, Ilsoo;Oh, Young-Tae;Hong, Doo-Pyo;Lee, Kang-Hoon
    • International Journal of Highway Engineering
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    • v.16 no.1
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    • pp.99-109
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    • 2014
  • PURPOSES : Climbing lanes on expressways managed by the Korea Expressway Corporation (KEC) have been hot potatoes due to conflicts between slow-moving vehicles such as trucks and other vehicles at the merging section as well as the less popularity with the slow-moving vehicles. In order to resolve such problems, KEC has altered existing climbing lanes to passing-type climbing lanes in 1999. The new type of climbing lanes showed an apparent improvement in mobility. For example, the speeds of vehicles using both climbing lane and other lanes improved a lot. However, there has been no clear evidence about improved safety. METHODS : This research effort was initiated to evaluate the safety of the new passing-type climbing lanes using the comparison-group(CG) method based on three-year-long traffic accident data sets before and after the change, respectively. RESULTS : The passing-type climbing lanes showed twice increased traffic accidents even though the traffic accidents on old type climbing lanes increased 1.1% during the same periods. In addition, in-depth study, the merging area of the passing-type climbing lanes was found out to be the weakest section where 43.8% traffic accidents out of total traffic accidents happened. It is noted that the merging area of the old type climbing showed only 25.0% traffic accidents. CONCLUSIONS : The new passing-type climbing lanes were found to be weak in terms of safety when compared with the old type climbing lanes. Especially, the merging area should be improved to reduce the risk of traffic conflicts between slow-moving vehicles and other vehicles.

Analysis of Elderly Drivers' Accident Models Considering Operations and Physical Characteristics (고령운전자 운전 및 신체특성을 반영한 교통사고 분석 연구)

  • Lim, Sam Jin;Park, Jun Tae;Kim, Young Il;Kim, Tae Ho
    • Journal of Korean Society of Transportation
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    • v.30 no.6
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    • pp.37-46
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    • 2012
  • The number of traffic accidents caused by elderly drivers over the age of 65 has surged over the past ten years from 37,000 to 274,000 cases. The proportion of elderly drivers' accidents has jumped 3.1 times from 1.2% to 3.7% out of all traffic accidents, and traffic safety organizations are pursuing diverse measures to address the situation. Above all, connecting safety measures with an in-depth research on behavioral and physical characteristics of elderly drivers will prove vital. This study conducted an empirical research linking the driving characteristics and traffic accidents by elderly drivers based on the Driving Aptitude Test items and traffic accident data, which enabled the measurement of behavioral characteristics of elderly drivers. In developing the Influence Model, we applied the zero-inflated Poisson (ZIP) regression model and selected an accident prediction model based on the Bayesian Influence in regards to the ZIP regression model and the zero-inflated negative binomial (ZINB) regression model. According to the results of the AAE analysis, the ZIP regression model was more appropriate and it was found that three variables? prediction of velocity, diversion, and cognitive ability? had a relation of influence with traffic accidents caused by elderly drivers.

Design of a designated lane enforcement system based on deep learning (딥러닝 기반 지정차로제 단속 시스템 설계)

  • Bae, Ga-hyeong;Jang, Jong-wook;Jang, Sung-jin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.236-238
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    • 2022
  • According to the current Road Traffic Act, the 2020 amendment bill is currently in effect as a system that designates vehicle types for each lane for the purpose of securing road use efficiency and traffic safety. When comparing the number of traffic accident fatalities per 10,000 vehicles in Germany and Korea, the number of traffic accident deaths in Germany is significantly lower than in Korea. The representative case of the German autobahn, which did not impose a speed limit, suggests that Korea's speeding laws are not the only answer to reducing the accident rate. The designated lane system, which is observed in accordance with the keep right principle of the Autobahn Expressway, plays a major role in reducing traffic accidents. Based on this fact, we propose a traffic enforcement system to crack down on vehicles violating the designated lane system and improve the compliance rate. We develop a designated lane enforcement system that recognizes vehicle types using Yolo5, a deep learning object recognition model, recognizes license plates and lanes using OpenCV, and stores the extracted data in the server to determine whether or not laws are violated.Accordingly, it is expected that there will be an effect of reducing the traffic accident rate through the improvement of driver's awareness and compliance rate.

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