Relevant bibliographies by topics / Road accident analysis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Road accident analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Road accident analysis"

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Zhang, Han Xin. "Analysis on Affection and Dissemination of Road Traffic Accidents." Advanced Materials Research 468-471 (February 2012): 200–203. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.200.

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Analysis for the road traffic accident is the dissemination of summary analysis of road traffic accidents, all types of traffic into the causes and recommends a system can reduce the effective theory of road traffic accidents. Road traffic system is a person, motor vehicles, the combined effect of the environment from the system. Road traffic safety depends on people, vehicles, roads, environment and road traffic management in all aspects of an integrated system for co-ordination. Characteristics for the occurrence of traffic accidents, road traffic accident on an analysis and research of the impact-spread of road traffic accident, to investigate the microscopic properties of a traffic accident on the traffic flow, emissions, noise impact and the dissemination of the law, analyzing the past, the scene of the accident the speed of other vehicles and drivers of the physical distribution psychological reaction to speed up the disposal of road traffic accidents, to reduce road traffic accidents on traffic flow and avoid the second derivative disasters, the elimination of road accident black spots, build a smart urban road traffic command system, to reduce pollutants in automobile exhaust emissions to protect the natural ecological environment, thus contributing to building a harmonious ecological city transport network.
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Bondar, Tetiana, Olga Belenchuk, Yevhen Tepliuk, and Oleksandr Pyna. "ACCIDENT ANALYSIS – THE WAY TO EFFECTIVE TRAFFIC SAFETY MANAGEMENT ON ROADS." Avtoshliakhovyk Ukrayiny, no. 2 (266) ’ 2021 (June 20, 2021): 46–52. http://dx.doi.org/10.33868/0365-8392-2021-2-266-46-52.

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Road safety management begins with a detailed analysis of accidents, which is reflected in Article 24 of the Law of Ukraine “On Road Traffic” which states that when performing repairs and maintenance of roads, streets and railway crossings road maintenance organizations in the first place should take measures for road safety on the basis of accounting and analysis of road accidents, results of inspections and surveys of roads, streets and railway crossings, and especially in emergency and dangerous areas and in places of concentration of road accidents. The problem of reducing the accident rate and reducing the number of victims of road accidents during the maintenance of roads has so far been solved mainly by identifying areas (places) of concentration of accidents with the development of measures to improve road conditions and improve the organization of traffic on them and conducting annual commission spring and autumn inspections of the road network by representatives of road organizations and the police. However, the areas of concentration of road accidents were not fully covered on the road network of local significance due to the lack of accurate reference of the places of accident in the accident registration cards, as well as they were not identified on the streets and roads of cities and other settlements due to the absence of any criteria for their identification and therefore the maximum efficiency from introduction of management of sites (places) of concentration of road accident isn’t reached. The article analyzes the criteria for determining the areas of concentration of accidents on public roads in different periods, examines the dynamics of the number of areas of concentration of accidents and considers other modern opportunities for effective traffic safety management, in particular, inspection (inspection) of existing roads.
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Nidhi. R, Ms, and Ms Kanchana V. "Analysis of Road Accidents Using Data Mining Techniques." International Journal of Engineering & Technology 7, no. 3.10 (July 15, 2018): 40. http://dx.doi.org/10.14419/ijet.v7i3.10.15626.

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Road Accident is an all-inclusive disaster with consistently raising pattern. In India according to Indian road safety campaign every minute there is a road accident and almost 17 people die per hour in road accidents. There are different categories of vehicle accidents like rear end, head on and rollover accidents. The state recorded police reports or FIR’s are the documents which contains the information about the accidents. The incident may be self-reported by the people or recorded by the state police. In this paper the frequent patterns of road accidents is been predicted using Apriori and Naïve Bayesian techniques. This pattern will help the government or NGOs to improve the safety and take preventive measures in the roads that have major accident zones.
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Sun, Chuan Jiao, Ru Yue Bai, and Yuan Yuan Yu. "Regression Analysis of Rural Road Traffic Accidents Causes." Applied Mechanics and Materials 97-98 (September 2011): 1042–45. http://dx.doi.org/10.4028/www.scientific.net/amm.97-98.1042.

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9238 traffic accidents data are collected in rural road of China. Through the data analysis, the main causes of rural road traffic accident are presented. The external environment, the participant features, road features and accident characteristics are involved. The regression analysis in SPSS is applied to find the relationship between the accident features. Overall, the rural road traffic accident was mainly due to in the rural area there are mass travel mode, lower grade roads, poorer safety awareness of traveler and the road is lack of traffic safety facilities and so on.
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Lemke, Kerstin. "Road Safety in Tunnels." Transportation Research Record: Journal of the Transportation Research Board 1740, no. 1 (January 2000): 170–74. http://dx.doi.org/10.3141/1740-22.

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Roads in tunnels differ from comparable open-road sections in many respects. For most drivers a tunnel is an unusual driving environment in the road network that might even cause stress. A safety analysis was carried out to estimate average accident rates and accident cost rates for different cross sections of tunnels on German roads. The analysis is based on all the available accident data for German freeway and highway tunnels reported to police. Personal injury accidents and material-damage-only accidents were analyzed separately. The findings indicate that accident rates are lower for roads in tunnels. Moreover, accidents with severe personal injury and material damage are less frequent on roads in tunnels. However, the fear of a maximum credible accident still remains.
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Akuh, Raymond, and Charles Atombo. "Road Transport Accident Analysis from A System-Based Accident Analysis Approach Using Swiss Cheese Model." International Journal of Engineering Education 1, no. 2 (December 15, 2019): 99–105. http://dx.doi.org/10.14710/ijee.1.2.99-105.

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Road safety has become a major concern to both developed and developing countries due to its negative economic impacts. Although, numerous approaches of accident analysis have been conducted, there seem to be an increase in road crashes every year. The main aim of this study is to analyse a driving school accident using a system-based accident analysis approach. The data for the study was collected using an interview. A Swiss Cheese Accident Causation Model was used to identify the factors that contributed to the accident. The study identified four weaknesses in the system defences of the driving school that created a possible accident trajectory. It is concluded that adopting system-based accident analysis approach in analysing road transport accidents, could lead to a greater understanding of latent conditions and road user error, which in turn could inform the development of intervention strategies within a road transport domain as suggested by other studies. Finally, the short falls of using only person approach of accident analysis in road transport domain are also highlighted.
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Meer, Jaffar Hussian, Sukhdeep Singh, and Komalpreet Singh. "Road Accidental Analysis and Identify the Black Spot." Volume 5 - 2020, Issue 8 - August 5, no. 8 (September 1, 2020): 871–76. http://dx.doi.org/10.38124/ijisrt20aug606.

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The increase in motor vehicles accompanied with expansion of roads has brought with it the challenge of addressing the adverse influence of road traffic accidents. Road incidents are a nationwide cataclysm with ever increasing trend which incurs a human health and development challenge and highly affect the human capital development of every nation. A mortality rate database (WHO, 2002) assures that India has highest number of accidents. Accident Black Spots are those locations on the road which have higher severity of accident either in terms of numbers or in terms of injuries. In this paper, efforts have been made to identify the location of accident black spots on national highway from singhpora pattan to panthachowk srinagar.The present era accidents are contributing major deaths worldwide due to increase in vehicular traffic.It has been estimated that every year 1.38 lakh lose their limbs and 6 lakh people get injured in road accidents in india.our country incurs a loss of 58000 crore each year due to road accidents. The most used roads to travel from jalandhar in punjab to uri in kashmir is NH-1A.The old name for NH-44 is NH-1A which was replaced after renumbering of all national highways in year 2010. In this report,the analysis includes study of some major accident spots or busy intersections in the NH-1A in between Pantha chowkh Srinagar to Singhpora Pattan.The study includes visiting sites,collecting required data for analysis and derives the results and remedies from what we had got. This report will be containing the material surveyed,pictures of road at different locations ,road details,figures,material for understanding of the unknown and finally the conclusion
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Nassar, S. A., F. F. Saccomanno, and J. H. Shortreed. "Road accident severity analysis: a micro level approach." Canadian Journal of Civil Engineering 21, no. 5 (October 1, 1994): 847–55. http://dx.doi.org/10.1139/l94-090.

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A comprehensive understanding of the relationship between road accident occurrence and severity of consequences permits the formulation of safety measures that are most cost-effective. A disaggregate model of road accident severity based on sequential logit models is presented. The sequential binary approach is able to account for the dependency between different levels of severity. Factors that affect the level of damage experienced by individuals involved in road accidents include the following: accident dynamics, seating position, vehicle condition, vehicle size, driver condition, and driver action. Separate models are calibrated for three accident situations: single-vehicle accidents, two-vehicle accidents, and multi-vehicle accidents. Ontario road accident police reports are used to calibrate and validate the models. The results of a simple application of the models to a safety protocol involving the effectiveness of passenger restraint devices are presented. Key words: road accident severity, personal injury, logit.
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Abdul Kudus Zaini and Abdussalam. "Potential Traffic Accident Analysis of Bangkinang – Rantau Berangin Road Riau Province, Indonesia." Journal of Innovation and Technology 2, no. 1 (April 25, 2021): 27–33. http://dx.doi.org/10.31629/jit.v2i1.3201.

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A traffic accident is an unexpected and unintentional event involving a vehicle with or without other road users, resulting in human casualties (minor injuries, serious injuries, and death) and property loss. In penel itian have taken vertebra way the segments road Bangkinang - Rantau Berangin KM 60 to KM 100 . This study aims for know se how much the level of traffic accidents in the area and for get The value of Accident Rate is Black Spot and Black Site on road Bangkinang-Rantau Berangin.The method used in this research is the Calculation Analysis method by identifying the Black Spot and Black Site based on the Accident Rate . The results of the analysis of data years 2014 - 2018 indicates that the segments road Bangkinang - Rantau Berangin can be identified value Accident rate which is Black Spot is the village of Pulau Gadang - Tanjung Alai with accident rate amounted to 2,069 and also the village of Tanjung Alai – Batu Bersurat with grades Accident rate amounted to 2,069. While for Accident rate against Black Site among others , namely the segment road Tanjung Alai – Batu Bersurat with Accident rate of 0.295 followed by the village of Pulau Gadang - Tanjung Alai is 0,258 and followed the village of Kuok - Village Lereng with Accident rate 0,240. From the analysis the researchers concluded that there are three locations which are the areas rawaan traffic accidents on roads Bangkinang - namely Rantau Berangin Village Tanjung Alai - Village Batu Bersurat , the village of Pulau Gadang - Tanjung Alai and villages Kuok - Village Lereng
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Fariska, Debi, and Sri Wiwoho Mudjanarko. "ANALYSIS OF TRAFFIC ACCIDENTS IN THE DISTRICT GRESIK (Case Study: Road Duduksampeyan Sta km 16 + 000 - Sta km 16 + 500)." IJEEIT : International Journal of Electrical Engineering and Information Technology 3, no. 2 (October 1, 2020): 1–7. http://dx.doi.org/10.29138/ijeeit.v3i2.1157.

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Traffic accident is an accident that occurs unexpectedly and unintentionally involving a vehicle which resulted in casualties and material damage. The problem of traffic accidents on the road Duduksampeyan Sta km 16 + 000 - Sta km 16 + 500 is the most significant. The purpose of this study was conducted to determine the level of traffic accidents that occurred in 2013-2018. This study uses a method that refers to the calculation of the number of accidents. The observations in the field of road safety facilities are still inadequate, lighting is in only one side of the road as much as ± 10 pieces, and the absence of traffic signs (speed limits, accident-prone areas, etc.). The volume of daily traffic averages on these roads as much as 3833 veh / hour. The results of the analysis carried accident rate by 158 the highest annual accident / km occurred in 2018. Meanwhile, based on the fatality index, it was 47.76%, the highest in 2013.
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Dissertations / Theses on the topic "Road accident analysis"

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Naji, Jamil Abdul-Rabb. "Road accident analysis in Yemen : the identification of shortcomings in road accident data, data adjustment, cost and development of road fatality model." Thesis, University of South Wales, 1996. https://pure.southwales.ac.uk/en/studentthesis/road-accident-analysis-in-yemen(8586c669-4709-4b2c-9d83-45003bc5d0bf).html.

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The true extent of the road accident problem in Yemen is questionable. Some agencies and citizens believe that the safety situation in Yemen is very critical while others disagree with this belief. Both sides however, agree that the road accident problem in Yemen is such that it requires considerable attention. Since Yemen has no history in road safety research and since there is no reliable road accident data in the country, making final judgements on the situation is difficult unless supported by adequate research. The aim of the present research is to provide a better understanding of the road accident problem in the Yemen. This can be made by investigation of the real dimensions of the road accident problem. This includes the identification of the shortcomings in road accident data, the cost of road accidents and modelling road accident fatalities.
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Mollet, C. J. "The analysis of road traffic accident data in the implementation of road safety remedial programmes." Thesis, Stellenbosch : Stellenbosch University, 2001. http://hdl.handle.net/10019.1/52483.

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Thesis (M.Ing.)--Stellenbosch University, 2001.
ENGLISH ABSTRACT: A road safety remedial programme has as an objective the improvement of road transportation safety by applying road safety engineering remedial measures to hazardous road network elements in a manner that will be economically efficient. Since accident data is the primary manifestation of poor safety levels it must be analysed in manner that will support the overall objective of economic efficiency. Three steps in the process of implementing a road safety remedial programme, that rely on the systematic analysis of accident data, are the identification of hazardous locations, the ranking of hazardous locations and the evaluation of remedial measure effectiveness. The efficiency of a road safety remedial programme can be enhanced by using appropriate methodologies to measure safety, identify and rank hazardous locations and to determine the effectiveness of road safety remedial measures. There are a number of methodologies available to perform these tasks, although some perform much better than other. Methodologies based on the Empirical Bayesian approach generally provide better results than the Conventional methods. Bayesian methodologies are not often used in South Africa. To do so would require the additional training of students and engineering professionals as well as more research by tertiary and other research institutions. The efficiency of a road safety remedial programme can be compromised by using poor quality accident data. In South Africa the quality of accident data is generally poor and should more attention be given to the proper management and control of accident data. This thesis will report on, investigate and evaluate Bayesian and Conventional accident data analysis methodologies.
AFRIKAANSE OPSOMMING: Die doel van 'n padveiligheidsverbeteringsprogram is om op die mees koste effektiewe manier die veiligheid van onveilige padnetwerkelemente te verbeter deur die toepassing van ingenieursmaatreëls. Aangesien padveiligheid direk verband hou met verkeersongelukke vereis die koste effektiewe implementering van 'n padveiligheidsverbeteringsprogram die doelgerigte en korrekte ontleding van ongeluksdata. Om 'n padveiligheidsverbeteringsprogram te implementeer word die ontleding van ongeluksdata verlang vir die identifisering en priortisering van gevaarkolle, sowel as om die effektiwiteit van verbeteringsmaatreëls te bepaal. Die koste effektiwiteit van 'n padveiligheidsverbeteringsprogram kan verbeter word deur die regte metodes te kies om padveiligheid te meet, gevaarkolle te identifiseer en te prioritiseer en om die effektiwiteit van verbeteringsmaatreëls te bepaal. Daar is verskeie metodes om hierdie ontledings te doen, alhoewel sommige van die metodes beter is as ander. Die 'Bayesian' metodes lewer oor die algemeen beter resultate as die gewone konvensionele metodes. 'Bayesian' metodes word nie. in Suid Afrika toegepas nie. Om dit te doen sal addisionele opleiding van studente en ingenieurs vereis, sowel as addisionele navorsing deur universiteite en ander navorsing instansies. Die gebruik van swak kwaliteit ongeluksdata kan die integriteit van 'n padveiligheidsverbeteringsprogram benadeel. Die kwaliteit van ongeluksdata in Suid Afrika is oor die algemeen swak en behoort meer aandag gegee te word aan die bestuur en kontrole van ongeluksdata. Die doel van hierdie tesis is om verslag te doen oor 'Bayesian' en konvensionele metodes wat gebruik kan word om ongeluksdata te ontleed, dit te ondersoek en te evalueer.
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Huang, Yu-Hsing. "Having a New Pair of Glassess : Applying Systemic Accident Models on Road Safety." Doctoral thesis, Linköpings universitet, CSELAB - Cognitive Systems Engineering Laboratory, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8189.

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The main purpose of the thesis is to discuss the accident models which underlie accident prevention in general and road safety in particular, and the consequences of relying on a particular model have for actual preventive work. The discussion centres on two main topics. The first topic is whether the underlying accident model, or paradigm, of traditional road safety should be exchanged for a more complex accident model, and if so, which model(s) are appropriate. From a discussion of current developments in modern road traffic, it is concluded that the traditional accident model of road safety needs replacing. An analysis of three general accident model types shows that the work of traditional road safety is based on a sequential accident model. Since research in industrial safety has shown that such model are unsuitable for complex systems, it needs to be replaced by a systemic model, which better handles the complex interactions and dependencies of modern road traffic. The second topic of the thesis is whether the focus of road safety should shift from accident investigation to accident prediction. Since the goal of accident prevention is to prevent accidents in the future, its focus should theoretically be on how accidents will happen rather than on how they did happen. Despite this, road safety traditionally puts much more emphasis on accident investigation than prediction, compared to areas such as nuclear power plant safety and chemical industry safety. It is shown that this bias towards the past is driven by the underlying sequential accident model. It is also shown that switching to a systemic accident model would create a more balanced perspective including both investigations of the past and predictions of the future, which is seen as necessary to deal with the road safety problems of the future. In the last chapter, more detailed effects of adopting a systemic perspective is discussed for four important areas of road safety, i.e. road system modelling, driver modelling, accident/incident investigations and road safety strategies. These descriptions contain condensed versions of work which has been done in the FICA and the AIDE projects, and which can be found in the attached papers.
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Chan, Wing-yee, and 陳詠怡. "An application of GIS for road accident analysis in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31224052.

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Chan, Wing-yee. "An application of GIS for road accident analysis in Hong Kong /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk:8888/cgi-bin/hkuto%5Ftoc%5Fpdf?B23294577.

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Berdica, Katja. "TraVIS for Roads - Examples of Road Transport Vulnerability Impact Studies." Doctoral thesis, KTH, Infrastructure, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3438.

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Tunaru, Radu. "Statistical modelling of road accident data via graphical models and hierarchical Bayesian models." Thesis, Middlesex University, 1999. http://eprints.mdx.ac.uk/8030/.

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The objective of this thesis is to develop statistical models for multivariate road accident data. Two directions of research are followed: graphical modelling for contingency tables cross-classified by accident characteristics, and hierarchical Bayesian models for multiple accident frequencies of different types modelled jointly. Multi-dimensional tables are analysed and it is shown how to use collapsibility to reduce the dimensionality of the analysis without the problems of Simpson's paradox. It is revealed that accident severity and the number of casualties are associated, and that these variables are mainly influenced by the number of vehicles and speed limit. Graphical chain models allow causal hypotheses to be formulated and it is shown how they are valuable tools for empirical research about road accident characteristics. The hierarchical Bayesian models developed combine generalized linear models with random effects. The novelty of these models consists in the joint modelling of multiple response variables. The models account for overdispersion and they are used for accident prediction and for ranking hazardous sites. All models are fully Bayesian and are fitted using Markov Chain Monte Carlo methods. It is shown that multiple response variables models are superior to separate univariate response models. Some theoretical problems are examined regarding the maximum likelihood estimation process for the two parameters negative binomial distribution. A condition is given that is equivalent with unique maximum likelihood estimators. The two directions of research are connected by using graphs to describe the models. In addition, a new Bayesian model selection procedure for contingency tables is proposed. This is based on Gibbs sampling and avoids problems associated with asymptotic tests. The conclusions revealed here can help practitioners to design better safety policies and to spend money more wisely on sites that really are dangerous.
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Johansson, Sofia, and Sri Vasireddy. "Analysis of Mobility and Traffic Safety with Respect to Changes in Volumes; Case Study: Stockholm, Sweden." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177780.

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The growing population and motorization generate more movements. In many cities, the increase of population and motorization is much greater than the development of the capacity of the transportation network. For unprotected road users, the risk of getting in a traffic accident increases and the risk of being more severely injured in an accident. In March 2020, a pandemic was declared because of a Coronavirus. More people started to work/study from home to prevent the virus from spreading by avoiding unnecessary trips, gatherings, and crowded areas. Therefore, travel behaviours have shifted during the pandemic compared to previous years. This project aims to get knowledge of how mobility and traffic accidents are affected by significant shifts of travel flow, predict the effect of traffic accidents based on mobility, and evaluate the risk of travelling on a particular road segment.

Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet

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Nováková, Kristýna. "Bezpečnostní inspekce na vybraných lokalitách v Olomouckém kraji." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2018. http://www.nusl.cz/ntk/nusl-372077.

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The diploma thesis focuses on a road safety inspection of selected intersections in Olomouc Region. The first step of the diploma thesis was to select 20 intersections, then each one was subjected to accident analysis. The intersections were compared by accident indicators, which were the basis of selection 11 intersections for visual inspection purposes. Based on visual inspections, the selection was further reduced to 4 intersections in Olomouc Region, which were subjected to detailed road safety inspection, then the potential risks influencing the origins of accident were identified and corrective measures were proposed in order to remove or eliminate the intersections problems.
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Brodňanská, Erika. "Speciální bezpečnostní inspekce na vybraných lokalitách v Jihomoravském kraji." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2017. http://www.nusl.cz/ntk/nusl-265585.

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The thesis focuses on a road safety inspection in South Moravian Region. In the first part, 15 locations with different characteristics were chosen, which were subjected to in-depth accident analysis and then compared by security indicators. On the basis of the results of this analysis, 5 locations were selected, namely the junction on a road II/430 and four sections on the roads II/373, II/384 and II/394. The selected sites were the objects for a road safety inspection, consisting of a personal visit of sections and the subsequent preparation of the potential risks influencing the origins of accidents. For each risk are proposed corrective measures that remove or eliminate the problems on selected section.
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Books on the topic "Road accident analysis"

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Chuvikov, Dmitriy. Models and algorithms for reconstruction and examination of emergency events of road accidents based on logical artificial intelligence. 2nd ed. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1220729.

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The purpose of the monograph is to create a methodology, combined expert and simulation models, as well as algorithms and software-modeling tools for reconstruction and examination of accident events for automating decision-making by an expert center employee. The methodology of combining and algorithms of joint work of an expert system based on logical artificial intelligence (mivar approach) and a simulation system for solving problems of reconstruction and examination of road accidents are developed; model reconstruction and examination of the accident in the formalism of the knowledge base bipartite oriented mivar nets, including analysis formulas braking qualities of the vehicle, determining the speed of a car's performance in terms of specific DTS, the formula for calculating different occasions: - slip car when braking, driving on curved sections of the road, hitting a car on the pedestrian in uniform motion and unlimited visibility; a method of generation of interfaces for designer expert systems based on the concept of mivar approach; special software in the form of expert systems "Analysis of road accident" in order to reduce the complexity of the process of calculating the disputed accidents, errors in the calculation and improve the accuracy and objectivity of the results obtained and the speed and quality of the calculations. It can be useful to specialists of expert institutions, insurance companies, educational institutions in the field of expertise, as well as unmanned vehicles in terms of objective analysis and examination of road accidents.
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Yajuan, Deng, ed. Lu wang huan jing xia gao su gong lu jiao tong shi gu ying xiang chuan bo fen xi yu kong zhi: Traffic accident impact analysis and control of expressway under road network. Beijing: Ke xue chu ban she, 2010.

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Ayati, Esmail. Rural road accidents in Iran: Analysis, comparison and the cost. Birmingham: Aston University. Department of Civil Engineering, 1988.

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Peirson, John. The Microeconomic analysis of the external costs of road accidents. Canterbury: University of Kent at Canterbury, 1996.

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Lee, Jinsun. Analysis of roadside accident frequency and severity and roadside safety management. [Olympia, Wash.]: Washington State Dept. of Transportation, 1999.

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Naim, Wassim G. Analysis of crossing path crashes. [Washington, D.C.]: National Highway Traffic Safety Administration, 2001.

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Strauss, Tim. Spatial scale of clustering of motor vehicle crash types and appropriate countermeasures. Ames, IA: Midwest Transportation Consortium, Iowa State University, 2009.

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Long, Dennis A. An analysis of off-highway haulage truck maintenance and repair accidents, 1978-84. Pittsburgh, Pa: U.S. Dept. of the Interior, Bureau of Mines, 1987.

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Souleyrette, Reginald R. Safety analysis of low-volume rural roads in Iowa. Ames, Iowa: Institute for Transportation, Iowa State University, 2010.

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Hauer, Ezra. Safety analysis of roadway geometry and ancillary features. Ottawa: Transportation Association of Canada = Association des transports du Canada, 1997.

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Book chapters on the topic "Road accident analysis"

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Ryan, G. Anthony. "Road Accident Prevention Research Unit, Accident Analysis and Prevention." In Transportation, Traffic Safety and Health — Man and Machine, 137–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57248-7_12.

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Dixit, Mrudul, Sai Deshmukh, Mannase Dongaonkar, and Snehal Jadhav. "Road accident analysis using random forest algorithm." In Recent Trends in Communication and Electronics, 502–6. London: CRC Press, 2021. http://dx.doi.org/10.1201/9781003193838-93.

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Jain, Sajal, Shrivatsa Krishna, Saksham Pruthi, Rachna Jain, and Preeti Nagrath. "Analysis of Road Accidents in India and Prediction of Accident Severity." In Data Management, Analytics and Innovation, 69–87. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2937-2_6.

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Li, Taoying, Yan Chen, Shengjun Qin, and Nan Li. "Highway Road Accident Analysis Based on Clustering Ensemble." In Computer Science for Environmental Engineering and EcoInformatics, 212–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22691-5_37.

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Wu, J., and L. Harbird. "Road accident analysis using a functional database language." In Lecture Notes in Computer Science, 241–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-57234-1_22.

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Singhal, Shruti, Bhavini Priyamvada, Rachna Jain, and Muskan Chawla. "Machine Learning Approach Towards Road Accident Analysis in India." In Algorithms for Intelligent Systems, 311–22. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-6707-0_29.

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Fernandes, Fábio A. O., Ricardo J. Alves de Sousa, and Mariusz Ptak. "Application of Numerical Methods for Accident Reconstruction and Forensic Analysis." In Head Injury Simulation in Road Traffic Accidents, 59–98. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89926-8_4.

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Yaacob, Nur Fatma Fadilah, Noradila Rusli, and Sharifah Norashikin Bohari. "A Review Analysis of Accident Factor on Road Accident Cases Using Haddon Matrix Approach." In Proceedings of the Second International Conference on the Future of ASEAN (ICoFA) 2017 – Volume 2, 55–65. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8471-3_6.

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Alteren, Bodil, Per Hokstad, Dagfinn Moe, and Kristian Sakshaug. "A Barrier Model for Road Traffic Applied to Accident Analysis." In Probabilistic Safety Assessment and Management, 3603–8. London: Springer London, 2004. http://dx.doi.org/10.1007/978-0-85729-410-4_576.

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Chandra, Sejal, Parmeet Kaur, Himanshi Sharma, Vaishnavi Varshney, and Medhavani Sharma. "In-Database Analysis of Road Safety and Prediction of Accident Severity." In Algorithms for Intelligent Systems, 277–83. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4936-6_31.

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Conference papers on the topic "Road accident analysis"

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Patil, Jayesh, Mandar Prabhu, Dhaval Walavalkar, and Vivian Brian Lobo. "Road Accident Analysis using Machine Learning." In 2020 IEEE Pune Section International Conference (PuneCon). IEEE, 2020. http://dx.doi.org/10.1109/punecon50868.2020.9362403.

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Hongguo, Xu, Zhang Huiyong, and Zong Fang. "Bayesian Network-Based Road Traffic Accident Causality Analysis." In 2010 WASE International Conference on Information Engineering (ICIE 2010). IEEE, 2010. http://dx.doi.org/10.1109/icie.2010.276.

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Yu, Qing, and Zhongyin Guo. "Road Traffic Accident Forecasts Based on Cointegration Analysis." In Fifth International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784479384.382.

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Hlaing, Kyi, Nyein Aung, Swe Hlaing, and Koichiro Ochimizu. "Performance Variability Analysis on Road Accident in Yangon." In 23rd International Conference on Enterprise Information Systems. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010451803290336.

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Patil, Jayesh, Vaibhav Patil, Dhaval Walavalkar, and Vivian Brian Lobo. "Road Accident Analysis and Hotspot Prediction using Clustering." In 2021 6th International Conference on Communication and Electronics Systems (ICCES). IEEE, 2021. http://dx.doi.org/10.1109/icces51350.2021.9489074.

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Kumar, Sachin, Vijay Bhasker Semwal, Vijender Kumar Solanki, Prayag Tiwari, and Denis Kalitin. "A Conjoint Analysis of Road Accident Data using K-modes Clustering and Bayesian Networks (Road Accident Analysis using clustering and classification)." In The Second International Conference on Research in Intelligent and Computing in Engineering. IEEE, 2017. http://dx.doi.org/10.15439/2017r44.

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Ren, Yu-Hui. "Analysis of Road Traffic Accident Caused by Human Error." In Second International Conference on Transportation Information and Safety. Reston, VA: American Society of Civil Engineers, 2013. http://dx.doi.org/10.1061/9780784413036.073.

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Haixia, Yang, and Nan Zhihong. "An application of factor analysis on road traffic accident." In Education (ICCSE 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccse.2010.5593713.

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Chaudhary, Roopal, Madhulika Bhadauria, and Anchal Garg. "Predictive analysis techniques for road accident injuries: A survey." In 2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon). IEEE, 2017. http://dx.doi.org/10.1109/smarttechcon.2017.8358349.

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Labib, Md Farhan, Ahmed Sady Rifat, Md Mosabbir Hossain, Amit Kumar Das, and Faria Nawrine. "Road Accident Analysis and Prediction of Accident Severity by Using Machine Learning in Bangladesh." In 2019 7th International Conference on Smart Computing & Communications (ICSCC). IEEE, 2019. http://dx.doi.org/10.1109/icscc.2019.8843640.

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