INTEGRATED ACCIDENT MODEL FOR MARINE CONVOY TRAFFIC IN ICE- COVERED WATERS

Independent safe navigation in ice-covered water is difficult. Icebreaker assistance is required for sailing through ice- covered waters. This poses an additional risk of collision. The study proposes a modified Human Factor Analysis and Classification (HFACS) framework to identify and classify contributing risk factors during a convoy. HFACS integration with Nagel-Schrekenberg (NaSch) model considers an operator’s behaviour and links it with the occurrence of various risk factors. The study finds significant influence in risk from small changes in two new factors, viz., crew reduction and crew overload. For example, based on the sensitivity analysis, it is determined that about a 17% contribution of crew reduction and about a 24% of contribution of crew overload increase the contribution of risk taking by an amount of approximately 93% in the overall risk of accidents. The accident probabilities obtained here will be helpful in decision making concerning safe operations during a convoy.

The Use of Expert Judgement Methods for Deriving Accident Probabilities in Aviation

Improving safety has always been the top interest in the aviation industry. The outcomes of safety and risk analyses have become much more thorough and sophisticated. They have become an industry standard of safety investigations in many airlines nowadays. In the past, airlines were much more limited in answering the questions about hazardous situations, accident probabilities, and accident rates. Airlines try hard to cope with stricter safety standards. The objective of this paper is to find out and quantify the extent of the expert judgment in helping airlines in the evaluation of the Flight Data Monitoring (FDM) events. On top of that, the paper reveals the method for a careful choice of experts, so that their estimations will maximize the potential of an accurate and useful outcome. Also, the paper provides details of implementation of the classical model into this research, then continues with the calculations and visualization of the outcomes. The outcomes are probability distributions per each aircraft type, then per IATA accident type and finally per FDM event.

Translating weather forecasts to road accident probabilities

<p>In Germany about 1000 severe road accidents are recorded by the police per day. On average, 8 % of these accidents are related to weather conditions, for example due to rain, snow or ice. In this study we compare several versions of a logistic regression models to predict hourly probabilities of such accidents in German administrative districts. We use radar, reanalysis and ensemble forecast data from the regional operational model of the German Meteorological Service DWD as well as police reports to train the model with different combinations of input datasets. By including weather information in the models, the percentage of correctly predicted accidents (hit rate) is increased from 30 % to 70 %, while keeping the percentage of wrongly predicted accidents (false-alarm rate) constant at 20 %. Accident probability increases nonlinearly with increasing precipitation. Given an hourly precipitation sum of 1 mm, accident probabilities are approximately 5 times larger at negative temperatures compared to positive temperatures. When using ensemble weather forecasts to predict accident probabilities for a leadtime of up to 21 h ahead, the decline in model performance is negligible. We suggest to provide impact-based warnings for road users, road maintenance, traffic management and rescue forces.</p>

How do Optimistic Individuals Affect Insurance Advertisements?

Some people have optimistic expectations regarding their accident probability, and thus, refrain from purchasing adequate insurance. This study investigates how insurance firms use advertisements to lower the ratio of optimistic individuals in the market. The main results are as follows: first, the optimal level of advertisements is maximized when the insurance premium is moderate. Second, the maximum level of advertisement varies according to the degree of optimism, which is measured by the difference between accurate and optimistic accident probabilities. Third, the advertisement decision is affected by the free-rider problem, and the equilibrium number of insurance firms with advertisement is always larger than that of firms without advertisement in a competitive insurance market.

Integrated Accident Model for Marine Convoy Traffic in Ice-Covered Waters

Independent safe navigation in ice-covered water is difficult. Icebreaker assistance is required for sailing through ice- covered waters. This poses an additional risk of collision. The study proposes a modified Human Factor Analysis and Classification (HFACS) framework to identify and classify contributing risk factors during a convoy. HFACS integration with Nagel-Schrekenberg (NaSch) model considers an operator’s behaviour and links it with the occurrence of various risk factors. The study finds significant influence in risk from small changes in two new factors, viz., crew reduction and crew overload. For example, based on the sensitivity analysis, it is determined that about a 17% contribution of crew reduction and about a 24% of contribution of crew overload increase the contribution of risk taking by an amount of approximately 93% in the overall risk of accidents. The accident probabilities obtained here will be helpful in decision making concerning safe operations during a convoy.

Predictive modeling of hourly probabilities for weather-related road accidents

An impact of weather on road accidents has been identified in several studies with a focus mainly on monthly or daily accident counts. We study hourly probabilities of road accidents caused by adverse weather conditions in Germany on the spatial scale of administrative districts. Meteorological predictor variables from radar-based precipitation estimates, high-resolution reanalysis and weather forecasts are used in logistic regression models. Models taking into account temperature and hourly precipitation sums reach the best predictive skill according to different metrics. By introducing meteorological variables, the models hit rate is increased from 0.3 to 0.7, while keeping the false alarm rate constant at 0.2. Accident probability has a non-linear relationship with precipitation. Given an hourly precipitation sum of 1 mm, accident probabilities are about 5 times larger at negative temperatures compared to positive temperatures. Based on ensemble weather forecasts skilful predictions of accident probabilities of up to 21 hours are possible; the loss of skill compared to a model using radar and reanalysis data is negligible. The findings are relevant in the context of impact based warnings for both road users, road maintenance and traffic management authorities, as well as rescue forces.

Estimating Rear-End Accident Probabilities with Different Driving Tendencies at Signalized Intersections in China

Rear-end accidents are the most common accident type at signalized intersections because of the different driving tendencies in the dilemma zone (DZ), where drivers are faced with indecisiveness of making “stop or go” decisions at yellow onset. In various researches, the number of vehicles in the DZ has been used as a safety indicator—the more the vehicles in the DZ, the higher the probability of rear-end accidents. However, the DZ-associated rear-end accident potential varies depending on drivers’ driving tendencies and the situations (position and speed) at the yellow onset. This study’s primary objective is to explore how the driving tendency impacts the DZ distribution and the probability of rear-end accidents. To achieve this, three types of driving tendencies were classified using K-means clustering analysis based on driving variables. Further, the boundary of the DZ is determined by logistic regression model of drivers’ stop/go decision. Then, we proposed the conditional probability model of rear-end accidents and developed a Monte Carlo simulation framework to calculate the model. The results indicate that the rear-end accident probability is dependent on the driving tendency even at the same position with the same speed in the DZ. The aggressive type has the highest risk probability followed by conservative and then the normal types. The quantitative results of the study can provide the basis for rear-end accident assessments.

The role of ship inspections in maritime accidents: An analysis of risk using the bow-tie approach

Ships are subject to inspections from different maritime stakeholders, such as port states, classification societies, shipowners, managers and operators. Each one implements their own inspection content depending on their role in the construction and operation phase of the vessel life cycle. Because few studies have investigated the influence of ship inspections on accidents, it is uncertain to which extent the current inspection regimes are contributing to reducing accidents. In addition, maritime risk analysis has, so far, not considered thoroughly the role of the inspection process in accident development. As a result, an improved understanding of the influence inspection methods would facilitate the implementation of effective measures for reducing accident probabilities or consequences. The approach used in this article involves identifying the underlying causes and the resulting consequences of accidents that may be associated with inspection issues and combining this knowledge in bow-tie representations. The developed bow-tie diagrams provide useful insights into the role of insufficient inspection practices in the development of maritime accidents and the severity of the resulting consequences. Furthermore, the developed diagrams may be used for investigating the risk from inspection issues by producing generic accident scenarios with every possible combination of the different parameters that describe all the possible pathways, from causes to consequences. Although this is a qualitative approach, it provides valuable insights into safety concerns that result from inspection practices and may also be used as a basis for further quantitative risk analysis.