• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.211-221
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• 2008

This dissertation studied the psychological cost, which converted the mental pain suffered by the victim of a traffic accident and his/her family, friends and people around him/her into social costs. Three methodologies - Choice Experiments, Direct Question and Dichotomous Choice Question - were used to design questionnaires, and models were built for each questionnaire design method. When building models, a logit model was used, which is used most frequently in probabilistic choice model. And the tobitmodel was used to make direct questionnaires. When verifying these models, although there were some differences in each model, suitability of most models and credibility of each coefficient were meaningful around the credibility level of 95%. According to the analysis, domestic psychological cost produced through the assessment model of psychological cost was 15.63 million won per person or 5.1 trillion in total, assuming 37.1% of total traffic accident cost.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.2
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• pp.75-86
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• 2010

The objective of this study is to suggest the process and method of local accident investigation for local authorities with a view to efficient and effective managing traffic accidents. With a project city selected accident-type maps, accident lists, accident diagrams, priority of black-spots/-lengths, site visits, remedial measures, opportunity costs, monitoring etc. are taken into consideration, by using accident data in the last 3 years. Analyzed are accident savings to be expected when applying technical, organizational, and administrative processes attached to local accident investigation.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.15-21
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• 2007

This paper proposes an improved methodology for estimating traffic accident cost savings in the transport appraisal. Four major problems from the existing framework are identified and their alternatives are suggested. First, casualties in the established approach are classified by just two types of 'killed' and 'injured'. This study supplies the indices of fatality further details. Namely, road victims are regrouped by 'killed', 'seriously injured', 'slightly injured', and 'accident reports'. Those of railways are similarly sorted by 'killed', 'seriously injured', and 'slightly injured'. Second, damage only accidents are not satisfactorily considered in the current arrangement. The accidents should be considered as one of the accident types and the social cost of them should also be evaluated. Third, the unit cost of accidents is given by the total value. The unit cost is consisted of several elements and each loss would be useful for a policy frame. This study breaks down the total figure into four pieces of costs, namely production loss, medical treatment, property loss, and administrative costs. Finally, there is inconsistency in the audit between roads and railways. Road accidents are analyzed by road types. On the other hand, patronage or others is the classification rule of rail accident costs. This paper suggests a way that the accident costs of two modes can be coherently estimated based on the level of services by each mode. The result of this study is expected to help frame more cautious social overhead capital investment policies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.33-43
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• 2022

The number of car crashes increases along with the increasing number of vehicles. Hence, diverse initiatives on traffic accidents have been implemented, targeting zero crash fatalities. According to the 3rd Traffic Safety Master Plan of 2016, the current standard selecting road accident black spots prioritizes locations with the high cumulative death toll. While this standard is suitable for roads that a city government manages to some extent, it is not suitable for roads less than 20 meters that a borough (Gu) handles. The roads under the supervision of a borough do not have enough death toll, and thus improvements on its road accident black spots are highly limited. In addition, discovering the causes of traffic accidents is not easy when the number of car accidents is obtained by considering only fatal accidents, which are relatively low in number. Therefore, including all traffic accidents might identify causes of accidents and result in better advancements. Therefore, this research follows rational decision-making and suggests new National Traffic Safety Master Plan standards. These new standards are obtained by comparing accident costs between the location of fatal crashes and road accident black spots. The analysis result shows that considering all types of accidents yields better results. For example, a Three-way Intersection in front of Zion Day Care Center, one of the selected spots under the current standard, has lower road crash costs than Sinchon Intersection, a selected spot under a new standard. Therefore, the study concludes that the standards to select road accident black spots need to include traffic accident severity and road crash costs.

• Journal of Korean Society of Transportation
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• v.35 no.1
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• pp.25-36
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• 2017

The purpose of this study is to analyze traffic accident reduction effect of the introduction of motorcycle safety inspection. To analyze the effect of motorcycle inspection, we first estimate the number of defective motorcycles, and calculate the probability of accident occurrences caused by the defect using four year traffic accident data. Finally, we estimate the number of reduced accidents due to the introduction of the inspection and the total reduced accident cost. In this study, we analyzed three scenarios. It is analyzed that when the safety inspection system is applied to all motorcycles, 642 cases of traffic accidents and 325 million won per year of traffic accident costs are reduced. It is approximately 0.1% of 2014 total traffic accident cost of 26.5725 trillion won per year. It suggests that the cost of traffic accidents and traffic accidents due to vehicle factors are reduced when the safety inspection system is introduced.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.125-136
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• 2005

The current traffic accident reduction procedure in economic feasibility study does not consider the characteristics of road and V/C ratio. For solving this problem, this paper suggests methods to be able to evaluate safety of each road in construction and improvement through developing accident Prediction model in reflecting V/C ratio Per road types and traffic characters. In this paper as primary process, model is made by tke object of urban roads. Most of all, factor effecting on accident relying on road types is selected. At this point, selecting criteria chooses data obtained from road planning procedure, traffic volume, existence or non-existence of median barrier, and the number of crossing point, of connecting road. and of traffic signals. As a result of analyzing between each factor and accident. all appear to have relatives at a significant level of statistics. In this research, models are classified as 4-categorized classes according to roads and V/C ratio and each of models draws accident predicting model through Poisson regression along with verifying real situation data. The results of verifying models come out relatively satisfactory estimation against real traffic data. In this paper, traffic accident prediction is possible caused by road's physical characters by developing accident predicting model per road types resulted in V/C ratio and this result is inferred to be used on predicting accident cost when road construction and improvement are performed. Because data using this paper are limited in only province of Jeollabuk-Do, this paper has a limitation of revealing standards of all regions (nation).

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.109-122
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• 2002

본 연구에서는 교차로의 비용 및 특성을 고려한 도로선형최적화 모형을 유전자 알고리즘(Genetic Algorithms)을 이용하여 개발하였다. 기존의 도로선형최적화 모형은 교차로 특성을 고려하지 못해서 실제 적용에 심대한 문제점을 내재하고 있다. 본 논문에서는 특정 도로선형에 교차로 건설의 필요가 있을 경우, 민감(Sensitive)하고 지배적인(Dominating) 교차로 비용 항목들 즉, 토공비용, 보상비, 포장비, 사고비용, 지체 및 연료소모비용 등의 산정이 시도되었다. 또한 비교적 우수한 도로선형 대안을 유전자 알고리즘을 이용한 탐색과정 중에서 비효율적으로 강제 퇴화시키는 단점 보완을 위한 교차로 국소 최적화 방법(Local Optimization of Intersections)이 개발되어 기존 모형을 보완하였다. 공간상의 도로선형은 매개변수적 묘사(Parametric Representation)를 통하여 구현하였으며 벡터운영(Vector Manipulation)을 통해 교차로비용 산정의 근간인 교차점과 다른 중요점들의 좌표를 찾을 수 있었다. 개발된 교차로 비용산정 모형이 보다 정밀하게 교차로 비용을 산정함이 증명되었으며 궁극적으로는 기존의 최적화 모형의 단점을 보완할 수 있음이 제시되었다. 또한, 새로이 제시된 교차로 국소 최적화 방법이 최적대안 탐색과정의 유연성을 증대하였으며, 결과적으로 효율적인 교차로의 유지에 기여함을 알 수 있었다. 제시된 교차로 국소 최적화 방법은 추후 단일노선이 아닌 도로망 최적화시의 기초를 제시함은 주목할 만 하다. 두개의 예제에서 도출된 최적노선 및 교차로 비용 등의 검토 결과, 도로상의 교차로 건설비용은 도로선형 최적화에 큰 영향을 미치는 실질적이며 민감한 비용 항목임이 검증되었으며 이는 도로선형최적화 모형이 교차로 비용을 반드시 검토 및 평가할 수 있어야 함을 반증한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.224-239
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• 2018

Autonomous vehicles can significantly reduce accidents due to 'driver's carelessness', which occupies the majority of causes for traffic accidents, but they may fail to avoid traffic accidents due to unexpected situations, such as "trolley dilemma", vehicle defects and road defects. Therefore in situations Autonomous vehicles need to be made ethical choices. This study assumes that Autonomous vehicles can not avoid traffic accidents due to unexpected sink holes. In this situation, the traffic accident costs was analyzed for the ethical choices of Autonomous vehicles. In the process, Autonomous vehicles were made to choose one of three ethical choices : (1) Egoism with priority on passenger safety, (2) Deontology for minimizing human damages, (3) Utilitarianism with minimizing traffic accident costs. As a result of the analysis, egoism had the highest traffic accident costs, and deontology for minimizing human damages had the lowest traffic accident costs.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.21-40
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• 2003

A traffic accident analysis method was developed and tested based on the highway alignment risk indices using geographic information systems(GIS). Impacts of the highway alignment on traffic accidents have been identified by examining accidents occurred on different alignment conditions and by investigating traffic accident risk indices(TARI). Evaluative criteria are suggested using geometric design elements as an independent variable. Traffic accident rates were forecasted more realistically and objectively by considering the interaction between highway alignment factors and the design consistency. And traffic accident risk indices and risk ratings were suggested based on model estimation results and accident data. Finally, forecasting traffic accident rates, evaluating the level of risk and then visualizing information graphically were combined into one system called risk assessment system by means of GIS. This risk assessment system is expected to play a major role in designing four-lane highways and developing remedies for highway sections susceptible to traffic accidents.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.351-360
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• 2010

In 2010, the number of registered vehicles reached almost at 17.48 millions in Korea. This dramatic increase of vehicles influenced to increase the number of traffic accidents which is one of the serious social problems and also to soar the personal and economic losses in Korea. Through this research, an enhanced intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network will be developed in order to obtain the important data for developing the countermeasures of traffic accidents and eventually to reduce the traffic accidents in Korea. Firstly, this research has investigated the influencing factors of road geometric features on the traffic volume of each approaching for the intersections where traffic accidents and congestions frequently take place and, a linear regression model of traffic accidents and traffic conflicts were developed by examining the relationship between traffic accidents and traffic conflicts through the statistical significance tests. Secondly, this research also developed an intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network through applying the intersection traffic volume, the road geometric features and the specific variables of traffic conflicts. Lastly, this research found out that the developed model is better than the existed forecasting models in terms of the reliability and accuracy by comparing the actual number of traffic accidents and the predicted number of accidents from the developed model. In conclusion, it is expect that the cost/effectiveness of any traffic safety improvement projects can be maximized if this developed intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network use practically at field in the future.