Journal articles: 'Accident modelling'

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MIKA, Otakar Jiří, and Pavel OTŘÍSAL. "Modelling of Accidental Impacts of Hazardous Chemical Substances in the Czech Republic." Challenges to national defence in contemporary geopolitical situation 2022, no. 1 (November 3, 2022): 135–42. http://dx.doi.org/10.47459/cndcgs.2022.16.

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The issue of major chemical accidents in the Czech Republic is first mentioned from a historical point of view. The following are the main hazardous impacts of chemical accidents. The next part is a comparison of the accidental impacts of major emergencies, such as toxic leakage, explosion and fire, even with examples of several typical chemical substances. Some factors of the main hazardous chemicals with a focus on toxic substances are discussed in detail. The modelling of accident impacts is presented in the next section on a detailed comparison of the accident impacts of nine main industrial chemical toxicants. The article also draws attention to the serious danger of the possible misuse of toxic substances in particular for hostile acts of chemical terrorism.

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Chaudhari, Dvij. "Modelling Road Accident using Poisson regression Models." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 4635–40. http://dx.doi.org/10.22214/ijraset.2021.35827.

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The objective of this research is to evaluate the safety of multi-lane urban roads in India. In this paper, a generalised linear modelling technique is applied for the analysis of the Indian Highway's road accident. The features of road, speed, and traffic data are analysed in Surat on four-lane urban roads. A novel approach to the model of accident prediction for an urban highway is being proposed to include daily average travel (ADT) and average spot speed (AS). The model was developed as a reliant variable and significant variables such as chain width, intersection no, ADT, AS, as separate variables for accidents per kilometre.. The results of the model provide a better assessment of accidents on a multilateral urban road. Because road accidents are different, statistical models do not adequately capture the characteristics of each section. As a result, the results of Poisson regression were the opposite of these variables. There was also no statistically significant type of traffic control. Significant statistically at level 0.05. Accident locations were assessed by correlating the severity of the accident with different attributes. This investigation will contribute to improving urban road safety.

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Pasculescu, Vlad Mihai, Marius Cornel Suvar, Ligia Ioana Tuhut, and Laurentiu Munteanu. "Numerical modelling of hydrogen release and dispersion." MATEC Web of Conferences 342 (2021): 01004. http://dx.doi.org/10.1051/matecconf/202134201004.

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Hydrogen is the most abundant element on earth, being a low polluting and high efficiency fuel that can be used for various applications, such as power generation, heating or transportation. As a reaction to climate change, authorities are working for determining the most promising applications for hydrogen, one of the best examples of crossborder initiative being the IPCEI (Important Project of Common European Interest) on Hydrogen, under development at EU level. Given the large interest for future uses of hydrogen, special safety measures have to be implemented for avoiding potential accidents. If hydrogen is stored and used under pressure, accidental leaks from pressure vessels may result in fires or explosions. Worldwide, researchers are investigating possible accidents generated by hydrogen leaks. Special attention is granted to the atmospheric dispersion after the release, so that to avoid fires or explosions. The use of consequence modelling software within safety and risk studies has shown its’ utility worldwide. In this paper, there are modelled the consequences of the accidental release and atmospheric dispersion of hydrogen from a pressure tank, using state-of-the-art QRA software. The simulation methodology used in this paper uses the “leak” model for carrying out discharge calculations. This model calculates the release rate and state of the gas after its expansion to atmospheric pressure. Accidental release of hydrogen is modelled by taking into account the process and meteorological conditions and the properties of the release point. Simulation results can be used further for land use planning, or may be used for establishing proper protection measures for surrounding facilities. In this work, we analysed two possible accident scenarios which may occur at an imaginary hydrogen refuelling station, accidents caused by the leaks of the pressure vessel, with diameters of 10 and 20 mm, for a pressure tank filled with hydrogen at 35 MPa / 70 MPa. Process Hazard Analysis Software Tool 8.4 has been used for assessing the effects of the scenarios and for evaluating the hazardous extent around the analysed installation. Accident simulation results have shown that the leak size has an important effect on the flammable/explosive ranges. Also, the jet fire’s influence distance is strongly influenced by the pressure and actual size of the accidental release.

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Yan, Linyang, and Sun-Woo Ko. "In-tunnel Accident Detection System based on the Learning of Accident Sound." Open Transportation Journal 15, no. 1 (May 21, 2021): 81–92. http://dx.doi.org/10.2174/1874447802115010081.

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Introduction: Traffic accidents are easy to occur in the tunnel due to its special environment, and the consequences are very serious. The existing vehicle accident detection system and CCTV system have the issues of low detection rate. Methods: A method of using Mel Frequency Cepstrum Coefficient (MFCC) to extract sound features and using a deep neural network (DNN) to learn sound features is proposed to distinguish accident sound from the non-accident sound. Results and Discussion: The experimental results show that the method can effectively classify accident sound and non-accident sound, and the recall rate can reach more than 78% by setting appropriate neural network parameters. Conclusion: The method proposed in this research can be used to detect tunnel accidents and consequently, accidents can be detected in time and avoid greater disasters.

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Igene, Oseghale Osezua, and Christopher Johnson. "To Computerised Provider Order Entry system: A comparison of ECF, HFACS, STAMP and AcciMap approaches." Health Informatics Journal 26, no. 2 (July 16, 2019): 1017–42. http://dx.doi.org/10.1177/1460458219859992.

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Different accident analytical approaches have been utilised in safety-critical industries for analysing accidents and formulating safety recommendations. This study presents a ‘health informatics’ case incident of a patient adversely affected due to a medication dosing error resulting from a combination of contributing factors including those relating to the Computerised Order Provider Entry System. A comparative study was carried out using selected accident analytical approaches: Human Factors and Classification System, System-Theoretic Accident Modelling and Processes and Accident Modelling. Each resulting output was compared using the model characteristic criteria developed by Underwood and Waterson. Safety recommendations developed based on the outputs from the models/methods were also compared for any similar findings. It was acknowledged that while accident models incorporating ‘systems thinking’ can prove to be beneficial for healthcare in providing insight on systemic factors, there is a need for improving the reliability and validity of these models. This particularly applies to Rasmussen’s Accident Modelling approach to be considered useful in the healthcare domain.

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Ma, Lu, Xuedong Yan, and Wenxin Qiao. "A Quasi-Poisson Approach on Modeling Accident Hazard Index for Urban Road Segments." Discrete Dynamics in Nature and Society 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/489052.

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In light of the recently emphasized studies on risk evaluation of crashes, accident counts under specific transportation facilities are adopted to reflect the chance of crash occurrence. The current study introduces more comprehensive measure with the supplement information of accidental harmfulness into the expression of accident risks which are also named Accident Hazard Index (AHI) in the following context. Before the statistical analysis, datasets from various sources are integrated under a GIS platform and the corresponding procedures are presented as an illustrated example for similar analysis. Then, a quasi-Poisson regression model is suggested for analyses and the results show that the model is appropriate for dealing with overdispersed count data and several key explanatory variables were found to have significant impact on the estimation of AHI. In addition, the effect of weight on different severity levels of accidents is examined and the selection of the weight is also discussed.

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Bogalecka, Magda. "Modelling Consequences of Maritime Critical Infrastructure Accidents." Journal of KONBiN 49, no. 2 (June 1, 2019): 477–95. http://dx.doi.org/10.2478/jok-2019-0046.

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Abstract The probabilistic general model of critical infrastructure accident consequences including the superposition of three models of the process of initiating events, the process of environment threats and the process of environment degradation is adopted to the maritime transport critical infrastructure. The general model is applied to this critical infrastructure accident with chemical release consequences identification and prediction. The model also includes the cost analysis of losses associated with these chemical releases. Further, under the assumption of the stress of weather influence on the ship operation condition, critical infrastructure accident losses are examined and the results are compared with the previous ones. Finally, the method of optimization are practically tested to the minimizing these losses and the procedures and the new strategy assuring lower environment losses of the considered critical infrastructure accidents are proposed.

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Al-Omari, Bashar H., and Eman S. Obaidat. "Analysis of Pedestrian Accidents in Irbid City, Jordan." Open Transportation Journal 7, no. 1 (February 22, 2013): 1–6. http://dx.doi.org/10.2174/1874447801307010001.

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The numbers of people who are walking and bicycling continues to increase all over the world and pedestrian accidents are becoming a serious problem in the developed and developing countries. However, the problem is more severe in the developing countries, such as Jordan where pedestrians represented 32.5% of all traffic accident fatalities and 23.8% of all traffic accident injuries during the year 2010. This study aims at analyzing pedestrian accidents in Irbid city, as an example for urban areas in Jordan, based on a total of 1090 pedestrian accidents that have occurred in the City during the three years period (1999 - 2001). The analysis was based on pedestrian characteristics, driver characteristics, accident time, accident location, weather, road surface condition, illumination condition, vehicle characteristics, speed limit, accident severity, pedestrian faults, and driver faults. Geographic Information System (GIS) tool was used to locate all pedestrian accidents over the study area. The results of the study showed that the majority of pedestrian accidents have occurred at non-intersection locations, during clear and sunny weather, on dry surface, during daylight, and at low speed limits. Also, more pedestrian accidents have occurred during the afternoons, on Thursdays, and during July. The majority of involved drivers in pedestrian accidents were males, with private license type, driving private vehicles and committed the fault of “not giving priority to pedestrians”. The majority of pedestrian victims were males, children less than 15 years old, and hit by vehicles while crossing the road.

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Morreale, A. C., M. J. Brown, and S. M. Petoukhov. "PRELIMINARY METHODOLOGY FOR THE ANALYSIS OF THE NATIONAL RESEARCH UNIVERSAL REACTOR USING INTEGRATED SEVERE ACCIDENT MODELLING CODES." AECL Nuclear Review 4, no. 1 (June 1, 2015): 53–65. http://dx.doi.org/10.12943/anr.2014.00035.

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The National Research Universal (NRU) Reactor is a multi-purpose research reactor located at Atomic Energy of Canada Limited (AECL) Chalk River Laboratories. The severe accident case for the NRU has been explored through deterministic and probabilistic safety analysis (PSA) including multi-level PSAs that detail the progression and consequences of a severe accident in the NRU. These previous calculations lack the interconnected and comprehensive features of a full severe accident modelling code that is now the standard for severe accident analysis of power reactors. It was of interest within AECL to evaluate modern severe accident modelling codes to the NRU reactor case to enhance the understanding of accident progression and predict the system damage and radiation release consequences of a severe accident, which is a very low probability event. The NRU is smaller and operates at a lower power than the large scale power reactors (e.g., pressurized heavy water reactors, pressurized water reactors, and boiling water reactors) that these codes were designed to analyze. Additionally, the NRU has a unique design different from the power reactors and several features relevant to severe accidents including filtered venting, large passive heat sinks, and a dispersion fuel design of uranium-silicide in an aluminum matrix. The major severe accident analysis codes available to AECL and their applicability to the NRU are explored in this paper. In addition, a preliminary strategy for employing the most applicable codes to the NRU for the purposes of severe accident modelling is proposed.

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Feizizadeh, Bakhtiar, Davoud Omarzadeh, Ayyoob Sharifi, Abolfazl Rahmani, Tobia Lakes, and Thomas Blaschke. "A GIS-Based Spatiotemporal Modelling of Urban Traffic Accidents in Tabriz City during the COVID-19 Pandemic." Sustainability 14, no. 12 (June 18, 2022): 7468. http://dx.doi.org/10.3390/su14127468.

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The main aim of the present study was to investigate the spatiotemporal trends of urban traffic accident hotspots during the COVID-19 pandemic. The severity index was used to determine high-risk areas, and the kernel density estimation method was used to identify risk of traffic accident hotspots. Accident data for the time period of April 2018 to November 2020 were obtained from the traffic police of Tabriz (Iran) and analyzed using GIS spatial and network analysis procedures. To evaluate the impacts of COVID-19, we used the seasonal variation in car accidents to analyze the change in the total number or urban traffic accidents. Eventually, the sustainability of urban transport was analyzed based on the demographic and land use data to identify the areas with a high number of accidents and its respective impacts for the local residences. Based on the results, the lockdown measures in response to the pandemic have led to significant reductions in road traffic accidents. From the perspective of urban planning, the spatiotemporal urban traffic accident analysis indicated that areas with high numbers of elderly people and children were most affected by car accidents. As we identified the hotspots of urban traffic accidents and evaluated their spatiotemporal correlation with land use and demography characteristics, we conclude that the results of this study can be used by urban managers and support decision making to improve the situation, so that fewer accidents will happen in the future.

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Grard, Aline, Etienne Everbecq, Pol Magermans, and Jean-François Deliège. "Modelling a Severe Transient Anoxia of Continental Freshwaters Due to a Scheldt Accidental Release (Sugar Industry)." Hydrology 8, no. 4 (November 28, 2021): 175. http://dx.doi.org/10.3390/hydrology8040175.

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Most anthropogenic pollution can be controlled, such as domestic and industrial releases, loads from agriculture, etc. However, some of them, which are associated to illegal discharges, industrial accidents, etc., are more difficult to forecast. This study was performed on the Tereos sugar industry accident that occurred during the night of 9 April 2020, when 88,000 cubic meters of effluents loaded with organic matter discharged in the Scheldt River (a 350 km long transnational river that flows through Northern France and Western Belgium). The accident had dramatic consequences on the receiving watercourse, over 120 km downstream. Fish mortalities have been observed and severe deoxygenation, reaching zero concentration in dissolved oxygen, have impacted river chemical quality. The objective was to understand and describe the dynamics of the chemical pollution and its propagation along the transboundary hydrographic network of the Scheldt. A method based on the processes of organic matter degradation in the river ecosystem was enhanced. It is demonstrated that the accident is doubtless the cause of the water column deoxygenation. This paper shows how the water quality modelling can help to understand and therefore to prevent the consequences of accidental pollution on a river network.

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Skalozubov, V., V. Spinov, D. Spinov, Т. Gablaya, V. Kochnyeva, and Yu Komarov. "SUBSTANTIATION OF MODERNIZED BLACKOUT & LOSS-OF-COOLANT ACCIDENT MANAGEMENT STRATEGY AT NUCLEAR POWER PLANTS WITH WWER." Odes’kyi Politechnichnyi Universytet Pratsi 2, no. 61 (2020): 70–77. http://dx.doi.org/10.15276/opu.2.61.2020.08.

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The analysis of the known results of RELAP5/V.3.2 simulation for loss of coolant & blackout accidents at WWER nuclear power plants showed that the design accident management strategies with design passive safety systems do not provide the necessary safety conditions for the maximum permissible temperature of fuel claddings, the minimum permissible level of coolant in the reactor and feed water in the steam generators. A conservative thermohydrodynamic model for a design and modernized blackout & loss-of-coolant accident management strategy at a nuclear power plant with WWER has been developed. Design passive safety systems carry out the design accident management strategy: pressurizer safety valves, secondary steam relief valves, and hydraulic reservoirs of the emergency core cooling system of the reactor. Promising afterheat removal passive systems and the reactor level and steam generator water level control systems carry out the modernized blackout & loss-of-coolant accident management strategy. The main conservative assumptions of the presented model of blackout & loss-of-coolant accidents: complete long-term failure of all electric pumps of active safety systems, the temperature of nuclear fuel in the central part of the fuel matrix is assumed as the maximum allowable one, effect of “run down” flow of a turbine feed pump and the coolant level in pressurizer on accident process is not considered. Computational modelling has found that violations of the safety conditions are over the entire range of leak sizes for the design blackout & loss-of-coolant accident management strategy. For the modernized blackout & loss-of-coolant accident management strategy, safety conditions are provided for 72 hours of the accident and more. The presented results of computational modelling of blackout accident management strategies for nuclear power plants can be used to modernize and improve symptom-informed emergency instructions and guidelines for the severe accident management at nuclear power plants with WWER. Application of the results of computational modelling of blackout accident management strategies is generally not substantiated for other types of reactor facilities. In this case, it is necessary to develop calculated models for blackout accident management taking into account the specifics of the structural and technical characteristics and operating conditions for safety related systems of nuclear power plants.

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Kuzmanić Skelin, Ana, Lea Vojković, Dani Mohović, and Damir Zec. "Weight of Evidence Approach to Maritime Accident Risk Assessment Based on Bayesian Network Classifier." Transactions on Maritime Science 10, no. 2 (October 21, 2021): 330–47. http://dx.doi.org/10.7225/toms.v10.n02.w07.

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Probabilistic maritime accident models based on Bayesian Networks are typically built upon the data available in accident records and the data obtained from human experts knowledge on accident. The drawback of such models is that they do not take explicitly into the account the knowledge on non-accidents as would be required in the probabilistic modelling of rare events. Consequently, these models have difficulties with delivering interpretation of influence of risk factors and providing sufficient confidence in the risk assessment scores. In this work, modelling and risk score interpretation, as two aspects of the probabilistic approach to complex maritime system risk assessment, are addressed. First, the maritime accident modelling is posed as a classification problem and the Bayesian network classifier that discriminates between accident and non-accident is developed which assesses state spaces of influence factors as the input features of the classifier. Maritime accident risk are identified as adversely influencing factors that contribute to the accident. Next, the weight of evidence approach to reasoning with Bayesian network classifier is developed for an objective quantitative estimation of the strength of factor influence, and a weighted strength of evidence is introduced. Qualitative interpretation of strength of evidence for individual accident influencing factor, inspired by Bayes factor, is defined. The efficiency of the developed approach is demonstrated within the context of collision of small passenger vessels and the results of collision risk assessments are given for the environmental settings typical in Croatian nautical tourism. According to the results obtained, recommendations for navigation safety during high density traffic have been distilled.

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Kumar, P., J. K. Jain, and G. Singh. "Accident prediction modelling for expressways: a review." IOP Conference Series: Materials Science and Engineering 1236, no. 1 (April 1, 2022): 012011. http://dx.doi.org/10.1088/1757-899x/1236/1/012011.

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Abstract Expressways are the need for fast movement of goods and human being for long distances in current scenario for every country, but at the same time these facilities have the highest severity rate among all the road categories. Various researchers around the world have tried to find out the effect of traffic volume, road geometry and environmental factors on frequency of accident on expressway by using different accident prediction modeling methods during last three decades. The purpose of this review paper is to find out the appropriate modeling method which can be used to predict accident frequency on the expressways in the developing country like India where traffic conditions, vehicular characteristics, and the driver behaviour are very different from the developing countries and to find out the research areas where the findings are inconclusive. Literature review suggests that among various models used so far, correlated random parameter model found to be the most advanced model to simultaneously account for both the heterogeneous effects of explanatory factors across the road segments and the cross correlations among the random parameter estimates. Findings related to variables like percentage of heavy vehicles, vertical gradient and lane width are not conclusive. However, safety effect of variables like speed limit, roadway lighting, pavement type and fog are less studied on expressway. The effect of allowing two wheelers on the expressways safety has not been studied yet, and the accidents related to fatigue or drowsiness also need examination.

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Bull, John P. "Data sources for accident modelling." Accident Analysis & Prevention 18, no. 2 (April 1986): 79–83. http://dx.doi.org/10.1016/0001-4575(86)90051-5.

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Maycock, G. "Accident modelling and economic evaluation." Accident Analysis & Prevention 18, no. 2 (April 1986): 169–74. http://dx.doi.org/10.1016/0001-4575(86)90061-8.

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Lee, Jae Yun, Young Geun Yoon, Tae Keun Oh, Seunghee Park, and Sang Il Ryu. "A Study on Data Pre-Processing and Accident Prediction Modelling for Occupational Accident Analysis in the Construction Industry." Applied Sciences 10, no. 21 (November 9, 2020): 7949. http://dx.doi.org/10.3390/app10217949.

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In the construction industry, it is difficult to predict occupational accidents because various accident characteristics arise simultaneously and organically in different types of work. Furthermore, even when analyzing occupational accident data, it is difficult to deduce meaningful results because the data recorded by the incident investigator are qualitative and include a wide variety of data types and categories. Recently, numerous studies have used machine learning to analyze the correlations in such complex construction accident data; however, heretofore the focus has been on predicting severity with various variables, and several limitations remain when deriving the correlations between features from various variables. Thus, this paper proposes a data processing procedure that can efficiently manipulate accident data using optimal machine learning techniques and derive and systematize meaningful variables to rationally approach such complex problems. In particular, among the various variables, the most influential variables are derived through methods such as clustering, chi-square, Cramer’s V, and predictor importance; then, the analysis is simplified by optimally grouping the variables. For accident data with optimal variables and elements, a predictive model is constructed between variables, using a support vector machine and decision-tree-based ensemble; then, the correlation between the dependent and independent variables is analyzed through an alluvial flow diagram for several cases. Therefore, a new processing procedure has been introduced in data preprocessing and accident prediction modelling to overcome difficulties from complex and diverse construction occupational accident data, and effective accident prevention is possible by deriving correlations of construction accidents using this process.

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Grabski, Franciszek. "Nonhomogeneous Poisson Process and Compound Poisson Process in the Modelling of Random Processes Related to Road Accidents." Journal of KONES 26, no. 1 (March 1, 2019): 39–46. http://dx.doi.org/10.2478/kones-2019-0005.

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Abstract The stochastic processes theory provides concepts and theorems that allow building probabilistic models concerning accidents. So called counting process can be applied for modelling the number of the road, sea and railway accidents in the given time intervals. A crucial role in construction of the models plays a Poisson process and its generalizations. The new theoretical results regarding compound Poisson process are presented in the paper. A nonhomogeneous Poisson process and the corresponding nonhomogeneous compound Poisson process are applied for modelling the road accidents number and number of injured and killed people in the Polish road. To estimate model parameters were used data coming from the annual reports of the Polish police [9, 10]. Constructed models allowed anticipating number of accidents at any time interval with a length of h and the accident consequences. We obtained the expected value of fatalities or injured and the corresponding standard deviation in the given time interval. The statistical distribution of fatalities number in a single accident and statistical distribution of injured people number and also probability distribution of fatalities or injured number in a single accident are computed. It seems that the presented examples explain basic concepts and results discussed in the paper.

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Andrijchenko, A. M., P. A. Yemushintsev, and V. V. Mikulich. "MODELING OF DYNAMICS OF PSYCHOLOGICAL STATE OF THE PERSONNEL OF DISABLED SUBMARINE IN DIFFERENT ACCIDENT PERIODS." Marine Medicine 6, no. 3 (September 30, 2020): 42–49. http://dx.doi.org/10.22328/2413-5747-2020-6-3-42-49.

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Aim: theoretical study and modelling of dynamics of psychological state of the personnel of disabled submarine in different accident periods.Materials and methods: theoretical analysis of literature sources in the context of psychological states of a person in emergency cases, including in seafarers divers, and materials describing chronology of accident progression at submarines.Results and discussion: from the results of analysis of studies of psychological states and available information about accidents at submarines, systematization of theoretical data was carried out and factors affecting the change of psychological states of submarine personnel in different accident periods were described.

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Fan, Shiqi, Zaili Yang, Eduardo Blanco-Davis, Jinfen Zhang, and Xinping Yan. "Analysis of maritime transport accidents using Bayesian networks." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 234, no. 3 (February 12, 2020): 439–54. http://dx.doi.org/10.1177/1748006x19900850.

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A Bayesian network–based risk analysis approach is proposed to analyse the risk factors influencing maritime transport accidents. Comparing with previous studies in the relevant literature, it reveals new features including (1) new primary data directly derived from maritime accident records by two major databanks Marine Accident Investigation Branch and Transportation Safety Board of Canada from 2012 to 2017, (2) rational classification of the factors with respect to each of the major types of maritime accidents for effective prevention, and (3) quantification of the extent to which different combinations of the factors influence each accident type. The network modelling the interdependency among the risk factors is constructed by using a naïve Bayesian network and validated by sensitivity analysis. The results reveal that the common risk factors among different types of accidents are ship operation, voyage segment, ship type, gross tonnage, hull type, and information. Scenario analysis is conducted to predict the occurrence likelihood of different types of accidents under various situations. The findings provide transport authorities and ship owners with useful insights for maritime accident prevention.

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Brzozowska-Rup, Katarzyna, and Marzena Nowakowska. "Modelling road traffic safety indices by means of regression with panel data." Engineering Management in Production and Services 12, no. 4 (December 1, 2020): 40–51. http://dx.doi.org/10.2478/emj-2020-0026.

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Abstract Although the occurrence of road accidents and the number of road accident casualties in almost all Polish voivodeships has decreased over the last few years, the rate of this change varies considerably from region to region. To provide a better understanding of such a tendency, panel data regression models are proposed to conduct this pilot research which evaluates the relative performance of Polish regions in terms of their road traffic safety. Panel data are multi-dimensional data which involve measurements over time. In the research, a voivodeship is a unit analysed at a group level, whereas a year is a unit analysed at a time level. A two-way error component regression model has been applied to survey the impact of regressors, the group effects, and time effects on a dependent variable. The analysis has been conducted using data acquired from the Statistics Poland Local Data Bank website, as well as from the General Directorate for National Roads and Motorways. The panel data from 16 regions in Poland and the 2012–2018 period have been investigated. The examined models refer to road traffic safety indices defined based on the following characteristics: the number of road accidents, the number road fatalities, and the number of people injured. The results of all the three models indicate a negative effect as regards the GDP per capita, (car) motorisation rate, the indicator of government expenditure for current maintenance of national roads, and the road length per capita. A positive association has been found between the truck motorisation rate and the indicator of local government expenditure on roads. The impact of the region's urbanisation indicators on road safety is ambiguous as, on the one hand, its increase causes a reduction in the road accident and accident injury indices, but, on the other hand, it produces a rise in the accident fatality index. In the models, the significance of time effects has been identified; a decreasing time trend suggests a general improvement in road safety from year to year. Most of the group effects have turned out to be highly significant. However, the effects differ as regards both the road accident and the accident injury indices in magnitude and direction.

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Bao, Juan, Wei Chen, Zhengtao Xiang, Yufeng Chen, and Yishui Shui. "Effect Analysis of Early Warning for Abandoned Object on Highway Based on Internet-of-Vehicles CA Model." Discrete Dynamics in Nature and Society 2018 (2018): 1–14. http://dx.doi.org/10.1155/2018/3821731.

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An early warning on the highway will effectively reduce traffic accidents. Considering the influence of an abandoned object on driving behavior, a Visual-based Asymmetric Two-lane Cellular Automata model with Abandoned Object (V-ATCA-AO) and an Internet-of-Vehicles-based Asymmetric Two-lane Cellular Automata model with Abandoned Object (IoV-ATCA-AO) are proposed. Based on the two models, two types of traffic accidents caused by an abandoned object are analyzed: rear-end collision caused by the abandoned object ahead and collision of the vehicle with the abandoned object. Simulation results show the following: (1) the accidents occur when the road density is smaller, while the accidents will not occur when the density is larger. The results are different from the rear-end collision rate curve without abandoned object in a single lane. (2) Compared with the visual-based avoidance pattern in V-ATCA-AO, the Internet-of-Vehicles-based avoidance pattern in IoV-ATCA-AO can create an early warning for the abandoned object and tell the vehicle to make an earlier lane change and decelerate in advance, thereby significantly reducing the accident rate. (3) Spatiotemporal characteristics in front of the abandoned object directly affect the accident rate: the less the “stability” of a traffic jam in front of the abandoned object, the higher the accident rate.

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Persaud, Bhagwant N. "Accident prediction models for rural roads." Canadian Journal of Civil Engineering 21, no. 4 (August 1, 1994): 547–54. http://dx.doi.org/10.1139/l94-056.

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Following on earlier work, the development of additional models for estimating the accident potential of rural road sections is described. In the modelling procedure presented, Ontario data are used to develop regression model estimates of a section's accident potential based on its traffic and geometric characteristics, and an empirical Bayesian procedure is used for refining these estimates using the section's accident count. These refined estimates are shown in a validation exercise to be superior to estimates based on accident counts or regression models only. This method of estimating accident potential is recommended for use in the identification of accident blackspots and in the evaluation of safety treatments on rural roads. To facilitate this use, detailed example applications are presented. Key words: safety, empirical Bayesian, accident prediction, rural roads, generalized linear modelling, accident modelling.

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Bolla, Margareth E., Tri Mardiyati Sir, and Putri D. K. Djahamouw. "Motorcycle accident modelling for the formulation of motorist safety action programs in Kupang City." MATEC Web of Conferences 270 (2019): 03017. http://dx.doi.org/10.1051/matecconf/201927003017.

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Kupang city had to deal with transport safety issues where the total number of traffic accidents in 2017 increased by 51.05% compared to 2011. This study aims to describe and analyze the factors that affect motorcycle accidents through modelling by the method of Generalized Linear Models with Genstat and SPSS programm. Based on the results of the police report data summary, accidents most often occur on Sunday (15.95%); the time span at 18:00 to 23:59 pm (45.94%); type of hit the front (35.68%); victims died (12.19%), male sex (80.71%); age range 18-25 years (37.20%); with the level of education at the level of Higher Education (42.38%); worked in the private sector (37.75%); do not have a driver's license (75.43%). The results of the analysis of survey data obtained equation modelling accident MCA = 0,0006713* Flow 0.000275*exp [0.2144 LaneWidth - ShoulderWidth_Sidewalk 1.952 - 2.026 MedianRoad + 0.2139 Speed + 0.0513 Access]. Modelling results showed that the addition of total lane width decrease the number of motorcycle accidents by 10% per year, pavement by 6% per year, median by 13% per year, traffic flow by 3% per year, speed by 14% per year, access road by 2% per year. It is therefore recommended a program of action in the form of additional elements of the road medians and pavement on a road segment that the accident rate can be reduced.

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El-Gheriani, Malak, Faisal Khan, Dan Chen, and Rouzbeh Abbassi. "Major accident modelling using spare data." Process Safety and Environmental Protection 106 (February 2017): 52–59. http://dx.doi.org/10.1016/j.psep.2016.12.004.

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Sheikh, Mohammad M. R. "Statistical Modelling of Road Traffic KSI Car Accidents in England (STATS19)." International Journal of Mathematics and Statistics Studies 10, no. 4 (April 15, 2022): 14–47. http://dx.doi.org/10.37745/ijmss.13/vol10n41447.

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Several generalised linear models for counts (i.e., Poisson Model) as well as for binary response (i.e., Binary Logistic Model) and ordinal response (i.e., Ordinal Logistic Model) depending on selected multiple explanatory factors (discrete/ categorical) were developed for the road KSI car accidents in England based on STATS19 data (that were manipulated and several new factors were created), after exploratory exploration of discrete/ dichotomous/ nominal/ ordinal factors applied graphical EDA techniques followed by univariate ANOVA/ ANCOVA as well as MANOVA/ MANCOVA based on same selected multiple explanatory factors. Only the main effects as well as two-way interactions were investigated. Majority of main effects and several interaction effects in GLM models were found statistically significant with greater or lesser likelihood of having consequences. The statistically significant KSI car accident factors were identified and quantified for leading to aims to reduce as well as to prevent the car accident, particularly the killed or seriously injured car accidents. It also leads to inform the policymakers on how best to reduce the number and severity of car crashes.

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Alzbutas, Robertas. "Probabilistic Dynamics for Integrated Analysis of Accident Sequences considering Uncertain Events." Science and Technology of Nuclear Installations 2015 (2015): 1–18. http://dx.doi.org/10.1155/2015/892502.

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The analytical/deterministic modelling and simulation/probabilistic methods are used separately as a rule in order to analyse the physical processes and random or uncertain events. However, in the currently used probabilistic safety assessment this is an issue. The lack of treatment of dynamic interactions between the physical processes on one hand and random events on the other hand causes the limited assessment. In general, there are a lot of mathematical modelling theories, which can be used separately or integrated in order to extend possibilities of modelling and analysis. The Theory of Probabilistic Dynamics (TPD) and its augmented version based on the concept of stimulus and delay are introduced for the dynamic reliability modelling and the simulation of accidents in hybrid (continuous-discrete) systems considering uncertain events. An approach of non-Markovian simulation and uncertainty analysis is discussed in order to adapt the Stimulus-Driven TPD for practical applications. The developed approach and related methods are used as a basis for a test case simulation in view of various methods applications for severe accident scenario simulation and uncertainty analysis. For this and for wider analysis of accident sequences the initial test case specification is then extended and discussed. Finally, it is concluded that enhancing the modelling of stimulated dynamics with uncertainty and sensitivity analysis allows the detailed simulation of complex system characteristics and representation of their uncertainty. The developed approach of accident modelling and analysis can be efficiently used to estimate the reliability of hybrid systems and at the same time to analyze and possibly decrease the uncertainty of this estimate.

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Quon, Tony K. S., and George E. Bushell. "Modelling Navigational Risk and Oil Spill Probabilities." Journal of Navigation 47, no. 3 (September 1994): 390–402. http://dx.doi.org/10.1017/s0373463300012339.

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This paper examines first a statistical modelling of the number of navigational accidents (collisons, groundings and strikings) involving tankers and freighters in Canadian waters; it then looks at a direct method of modelling oil spill frequency and magnitude, given a navigational accident. The former is used to examine various hypotheses in the literature regarding the impact of various factors on navigational risk. The latter is based on a direct probability tree analysis which allows the estimation of detailed oil spill impacts by facilitating the examination of representative spill sizes.

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Zerka, Abdelaziz, and Fouad Jawab. "Modelling the costs of pre-hospital transport service for victims of road accidents in TDABC." Archives of Transport 61, no. 1 (March 31, 2022): 89–101. http://dx.doi.org/10.5604/01.3001.0015.8197.

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The pre-hospital transport of victims of road accidents in Morocco by basic ambulances concerns the majority of the population of victims requiring urgent care. It also constitutes the common service that benefits the entire population of victims, in terms of pre-hospital care. The objective of this contribution is to develop a model for calculating the costs of pre-hospital transport of road accident victims using Time-Driven Activity-Based Costing (TDABC). This model could be effective in better understanding how consumption occurs and how resources are administered and distribut-ed within the pre-hospital care service portfolio. The qualitative research approach that we have adopted in the con-text of this study has enabled us to map and identify all the activities and tasks carried out in the process of pre-hospital transport of road accident victims. The model obtained is flexible enough to adapt to the various situations of pre-hospital transport of road accident victims by basic ambulances. The application of this model in the Moroccan context, delimited in a well-defined round trip (civil protection - accident site - hospital - civil protection) demonstrates that the said model is valid for cost calculation. The calculations made (217.47 MAD, 224.31 MAD, 225.45 MAD and 226.59 MAD) allow us to identify the possible cases of victims transported by basic ambulance. However, the TDABC, applied to the pre-hospital transport of road accident victims, has some limitations, in particular the estimation of time which is the main key to the allocation of the consumed resources. The results show that the TDABC promotes a better knowledge of all the processes related to the pre-hospital transport service. It allows making visible the value of the costs of the victims of road accidents in the selected patient population. Indeed, when the model is used in the set of routes (black points), decision makers are able to see, on the one hand, the variation of costs between similar pre-hospital transport services and different routes for the same transport services and, on the other hand, the value of the costs of each category of road accident victims' population.

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Wan Yaacob, Wan Fairos, and Wan Zakiyatussariroh Wan Husin. "Modelling Malaysian Road Accident Deaths : An Econometric Approach." Social and Management Research Journal 3, no. 1 (June 1, 2006): 99. http://dx.doi.org/10.24191/smrj.v3i1.5105.

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A number of methods have been proposed for dealing with road accident death model. This paper uses econometric regression models to develop the road accident death model. By using this approach, this paper attempts to establish a statistical model to describe the relationship between the total road accident deaths and a range ofexplanatory macroeconomic variables. The macroeconomic factors used in the model include population, the number of registered vehicles, road length, technique of data coverage, system of data recording and Gross Domestic Product. The results suggest that the POp, ROADL, VEH and DR do not have any impact on road accident deaths. In contrast, the GDP and Technique of data Coverage were found to be highly significant (P < 0.05) in explaining the road accident deaths.

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Zhang, Yue, Yajie Zou, Lingtao Wu, Jinjun Tang, and Malik Muneeb Abid. "Exploring the Application of the Linear Poisson Autoregressive Model for Analyzing the Dynamic Impact of Traffic Laws on Fatal Traffic Accident Frequency." Journal of Advanced Transportation 2020 (October 9, 2020): 1–9. http://dx.doi.org/10.1155/2020/8854068.

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Annual fatal traffic accident data often demonstrate time series characteristics. The existing traffic safety analysis approaches (e.g., negative binomial (NB) model) often cannot accommodate the dynamic impact of factors in fatal traffic accident data and may result in biased parameter estimation results. Thus, a linear Poisson autoregressive (PAR) model is proposed in this study. The objective of this study is to apply the PAR model to analyze the dynamic impact of traffic laws and climate on the frequency of fatal traffic accidents occurred in a large time span (from 1975 to 2016) in Illinois. Besides, the NB model, NB with a time trend, and autoregressive integrated moving average model with exogenous input variables (ARIMAX) are also developed to compare their performances. The important conclusions from the modelling results can be summarized as follows. (1) The PAR model is more appropriate for analyzing the dynamic impacts of traffic laws on annual fatal traffic accidents, especially the instantaneous impacts. (2) The law that allows motorcycles and bicycles to proceed on a red light following the rules applicable after a “reasonable period of time” leads to an increase in the frequency of annual fatal traffic accidents by 14.98% in the short term and 30.69% in the long term. The climate factors such as average temperature and precipitation concentration period have insignificant impacts on annual fatal traffic accidents in Illinois. Thus, the modelling results suggest that the PAR model is more appropriate for annual fatal traffic accident data and has an advantage in estimating the dynamic impact of traffic laws.

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Liang, Guohua, Xujiao Sun, Yidan Zhang, Mingli Chen, and Wanting Zhang. "Identifying Expressway Accident Black Spots Based on the Secondary Division of Road Units." Promet - Traffic&Transportation 33, no. 5 (October 8, 2021): 731–43. http://dx.doi.org/10.7307/ptt.v33i5.3680.

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For the purpose of reducing the harm of expressway traffic accidents and improving the accuracy of traffic accident black spots identification, this paper proposes a method for black spots identification of expressway accidents based on road unit secondary division and empirical Bayes method. Based on the modelling ideas of expressway accident prediction models in HSM (Highway Safety Manual), an expressway accident prediction model is established as a prior distribution and combined with empirical Bayes method safety estimation to obtain a Bayes posterior estimate. The posterior estimated value is substituted into the quality control method to obtain the black spots identification threshold. Finally, combining the Xi'an-Baoji expressway related data and using the method proposed in this paper, a case study of Xibao Expressway is carried out, and sections 9, 19, and 25 of Xibao Expressway are identified as black spots. The results show that the method of secondary segmentation based on dynamic clustering can objectively describe the concentration and dispersion of accident spots on the expressway, and the proposed black point recognition method based on empirical Bayes method can accurately identify accident black spots. The research results of this paper can provide a basis for decision-making of expressway management departments, take targeted safety improvement measures.

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Zhang, Zhihao, Wenzhong Yang, and Silamu Wushour. "Traffic Accident Prediction Based on LSTM-GBRT Model." Journal of Control Science and Engineering 2020 (March 5, 2020): 1–10. http://dx.doi.org/10.1155/2020/4206919.

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Road traffic accidents are a concrete manifestation of road traffic safety levels. The current traffic accident prediction has a problem of low accuracy. In order to provide traffic management departments with more accurate forecast data, it can be applied in the traffic management system to help make scientific decisions. This paper establishes a traffic accident prediction model based on LSTM-GBRT (long short-term memory, gradient boosted regression trees) and predicts traffic accident safety level indicators by training traffic accident-related data. Compared with various regression models and neural network models, the experimental results show that the LSTM-GBRT model has a good fitting effect and robustness. The LSTM-GBRT model can accurately predict the safety level of traffic accidents, so that the traffic management department can better grasp the situation of traffic safety levels.

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Klockner, Karen, and Yvonne Toft. "Railway accidents and incidents: Complex socio-technical system accident modelling comes of age." Safety Science 110 (December 2018): 59–66. http://dx.doi.org/10.1016/j.ssci.2017.11.022.

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Griffin, T. G. C., M. S. Young, and N. A. Stanton. "Investigating accident causation through information network modelling." Ergonomics 53, no. 2 (January 22, 2010): 198–210. http://dx.doi.org/10.1080/00140130903125165.

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Hale, R. E. "Real-Time Modelling of HFIR Accident Releases." Radiation Protection Dosimetry 73, no. 1 (September 1, 1997): 155–57. http://dx.doi.org/10.1093/oxfordjournals.rpd.a032122.

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Kraan, B. C. P., and R. M. Cooke. "Processing Expert Judgements in Accident Consequence Modelling." Radiation Protection Dosimetry 90, no. 3 (August 2, 2000): 311–15. http://dx.doi.org/10.1093/oxfordjournals.rpd.a033153.

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Yannis, George, Aggeliki Kanellopoulou, Kallia Aggeloussi, and Dimitrios Tsamboulas. "Modelling driver choices towards accident risk reduction." Safety Science 43, no. 3 (March 2005): 173–86. http://dx.doi.org/10.1016/j.ssci.2005.02.004.

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Baksh, Al-Amin, Faisal Khan, Veeresh Gadag, and Refaul Ferdous. "Network based approach for predictive accident modelling." Safety Science 80 (December 2015): 274–87. http://dx.doi.org/10.1016/j.ssci.2015.08.003.

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Guedes Soares, C., and Enrico Zio. "Accident modelling and prevention at ESREL 2006." Accident Analysis & Prevention 41, no. 6 (November 2009): 1131–32. http://dx.doi.org/10.1016/j.aap.2009.04.008.

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Huang, Mingxia, Baoyun Sun, Yu Ling, Zhang Pan, Yitong Zhan, and Siyu Jia. "Modelling of traffic capacity under traffic accident." International Journal of Simulation and Process Modelling 14, no. 6 (2019): 500. http://dx.doi.org/10.1504/ijspm.2019.10027913.

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Ling, Yu, Zhang Pan, Yitong Zhang, Siyu Jia, Baoyun Sun, and Mingxia Huang. "Modelling of traffic capacity under traffic accident." International Journal of Simulation and Process Modelling 14, no. 6 (2019): 500. http://dx.doi.org/10.1504/ijspm.2019.106188.

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Krašna, S., I. Prebil, and M. Hribernik. "Human body modelling for traffic accident analysis." Vehicle System Dynamics 45, no. 10 (October 2007): 969–80. http://dx.doi.org/10.1080/00423110701538296.

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Al-shanini, Ali, Arshad Ahmad, and Faisal Khan. "Accident modelling and analysis in process industries." Journal of Loss Prevention in the Process Industries 32 (November 2014): 319–34. http://dx.doi.org/10.1016/j.jlp.2014.09.016.

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Šadek, Siniša, and Davor Grgić. "NPP Krško containment modelling with the ASTEC code." Journal of Energy - Energija 64, no. 1-4 (June 29, 2022): 163–77. http://dx.doi.org/10.37798/2015641-4150.

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ASTEC is an integral computer code jointly developed by Institut de Radioprotection et de Sûreté Nucléaire (IRSN, France) and Gesellschaft für Anlagenund Reaktorsicherheit (GRS, Germany) to assess nuclear power plant behaviour during a severe accident (SA). The ASTEC code was used to model and to simulate NPP behaviour during a postulated station blackout accident in the NPP Krško. The accident analysis was focused on containment behaviour; however the complete integral NPP analysis was carried out in order to provide correct boundary conditions for the containment calculation. During the accident, the containment integrity was challenged by release of reactor system coolant through degraded coolant pump seals, molten corium concrete interaction and direct containment heating mechanisms. Impact of those processes on relevant containment parameters, such as compartments pressures and temperatures, is going to be discussed in the paper.

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Tautkus, Arūnas, and Algirdas Jurkauskas. "THE ESTABLISHMENT OF CIRCUMSTANCES AND EVIDENCES OF AN ACCIDENT AND THEIR APPLICTION IN RESEARCH." TRANSPORT 18, no. 2 (April 30, 2003): 72–78. http://dx.doi.org/10.3846/16483840.2003.10414069.

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An accident depends on a lot of factors and circumstances. The estabilishment of factors, different evidences and circumstances are very important for research. Some important evidences are fixed when we make photos, do the the measurements of the deformation of means of transport, do the measurements of sliding and of stopping, estimate the condition of road and weather, driver's and pedestrian's actions, do cross-examination of witnesses and so on. We often have no result even if we know the main circumstances of the accident. So we need some engineer countings for the modelling of various situations. The method of linear momentum is presented in this article. It is used for the counting of parameters of accidents. The accident diagram gives information for us. We can do the research of an accident with the help of this method and software. So the research into the collision of cars was done with the help of this method and software.

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Pelenyte-Vyšniauskiene, Lina, and Algirdas Jurkauskas. "RESEARCH INTO OCCUPANT'S MOTION IN VEHICLES DURING CRASHES." TRANSPORT 19, no. 4 (August 31, 2004): 184–90. http://dx.doi.org/10.3846/16484142.2004.9637974.

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Traffic accidents depend on many factors and circumstances. Important data are registered by taking photos of the accident place, measuring the deformations of vehicles and skidding and sliding traces. Weather conditions, drivers’ and pedestrian's actions are also taken into account. However the existing data are far from sufficient to conduct a research into traffic accidents. In such cases mathematical modelling and the application of computer programs are very helpful. This article deals with the processes during the collision of vehicles as well as the occupant's dynamics inside the vehicle. The research studies on what the occupant motion depends and what is the power balance between the occupant and safety means. The article offers a way of evaluating injuries, measuring the occupants’ acceleration and velocity, taking into account different distances inside the vehicle during an accident.

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Brandt, J., J. H. Christensen, and L. M. Frohn. "Modelling transport and deposition of caesium and iodine from the Chernobyl accident using the DREAM model." Atmospheric Chemistry and Physics Discussions 2, no. 3 (June 24, 2002): 825–74. http://dx.doi.org/10.5194/acpd-2-825-2002.

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Abstract. A tracer model, DREAM (the Danish Rimpuff and Eulerian Accidental release Model), has been developed for modelling transport, dispersion and deposition (wet and dry) of radioactive material from accidental releases, as the Chernobyl accident. The model is a combination of a Lagrangian model, that includes the near source dispersion, and an Eulerian model describing the long-range transport. The performance of the transport model has previously been tested within the European Tracer Experiment, ETEX, which included transport and dispersion of an inert, non-depositing tracer from a controlled release. The focus of this paper is the model performance with respect to the deposition of 137Cs, 134Cs and 131I from the Chernobyl accident, using different relatively simple and comprehensive parameterizations. The performance, compared to measurements, of different combinations of parameterizations of wet and dry deposition schemes has been evaluated, using different statistical tests.

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Omar Mohamed, Buseif, Nur Izzi Yusoff, Muhammad Mubaraki, and Sri Atmaja Rosyidi. "Statistical Overview of Factors Influencing Traffic Accidents Severity On El-Brega Coastal Freeway in Libya." Open Transportation Journal 13, no. 1 (September 26, 2019): 154–61. http://dx.doi.org/10.2174/1874447801913010154.

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Background: Globally, Road Traffic Accidents (RTAs) are one of the significant causes of fatality and injury. In Libya, RTAs have resulted in disabilities and were the third leading cause of death. However, there is a lack of information on RTAs and road safety in Libya. Objective: The present study aims to fill the knowledge gap by performing a statistical analysis to identify the factors associated with road accident severity in El-Brega Coastal Freeway. Methods: RTAs data extracted from police investigation reports in Ajdabiya Municipality for the period from 2001 to 2010. Then descriptive analysis and Binary logistic regression model (BLM) are applied to analyzing the data. Results: Descriptive analysis results showed that between 2001 and 2010, approximately 45% of RTAs in Ajdabiya Municipality occurred on El-Brega Coastal Freeway, and more than 1225 individuals lost their lives or sustained injuries in these RTAs. Furthermore, Sixty-two percent (n = 137) of those who died in accidents were from the 20–45 age group. BLM Results concluded that only eight predictors have statistical significant with accident injury severity. Five of them increase the likelihood of injury severity. A head-on collision is the prime influence factor to increase injury severity odds, followed by high-speed driving, Weekends, horizontal curves, and driver’s age. While accident injury tends to be less severe with the other predictors like rollover collision, rear-end collision, and accidents involving animals. Conclusion: Thus, implementing the use of seat-belt and speed control regulations, with activating ambulance services are the urgent countermeasures to enhance road safety.

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Septianingtyas, Daniar Mukti. "IDENTIFYING THE CHARACTERISTICS OF TRAFFIC ACCIDENT VICTIMS IN SIDOARJO IN 2016." Indonesian Journal of Public Health 14, no. 1 (July 5, 2019): 50. http://dx.doi.org/10.20473/ijph.v14i1.2019.51-61.

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Traffic accident becomes a very serious case because it causes not only material loss but also physical and psychological harms to the subject and the people around him. Accidents that occurred resulted in not only injuries but also death. This study aims to identify characteristics of traffic accident victims in Sidoarjo in 2016. It was an observational study with cross sectional design and based on daily data of traffic accident with 735 samples. Data were processed by ordinal logistic regression statistic test. In this case, variables of the study included the severity of victim, age, gender, profession, time of occurrence, type of collision, and type of vehicle. The results of characteristic identification showed that most of the victims had minor injuries, were male, aged ≥ 34 years old, workers, and got into accidents in the afternoon. The conclusion was factors affecting the severity of traffic accident victims in Sidoarjo were head-on-collisions (hitting straight) and motorcycles as the vehicle type. Modelling obtained was 3,133 for the constant of head-on-collision (hitting straight), 1,464 for the constant of vehicle type (motorcycles), and Y value of 4,597. This study was not supported by complete predictor data, thus the data need to be added so that the accuracy of classification increases and the value gets significant.

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Journal articles on the topic 'Accident modelling'

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