Association Rules to Identify Factors Affecting Risk and Severity of Road Accidents

Makarova, Irina; Yakupova, Gulnara; Buyvol, Polina; Mukhametdinov, Eduard; Pashkevich, Anton

doi:10.5220/0009836506140621

Cited by 10 publications

(4 citation statements)

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“…It allows to identify common sets of objects in a large collection [16]. Association rules have previously been successfully used to predict customer purchases, help diagnose diseases, analyze and predict telecommunications equipment failures, analyze web page visits [17], and identify factors that affect the likelihood and severity of road traffic accidents [18]. The main advantage of association rules is such a form of calculations results presentation, which is easy for human perception and is available for interpretation by programming languages [19].…”

Section: Theory: Methods Used In the Analysis Of Vehicle Reliabilitymentioning

confidence: 99%

Application of intelligent analysis to identify defective vehicle components

Voroshilov

Buyvol

2021

MATEC Web Conf.

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The article shows the possibility of using intelligent analysis in a vehicle service when assessing the vehicle reliability. It was hypothesized that the use of association rules in diagnostics can increase the speed of repairs and the quality of customer service, allowing to identify the nodes that are highly likely to be faulty at the same time. For this, a knowledge base was built from the patterns obtained by applying association rules to the vehicle failure statistics. An application was implemented, which, on its basis, issues recommendations to the repair worker to check certain nodes based on the already identified defective nodes entered into the program. The proposed technique, together with the developed software tool, will optimize the diagnostic processes.

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Section: Theory: Methods Used In the Analysis Of Vehicle Reliabilitymentioning

confidence: 99%

Application of intelligent analysis to identify defective vehicle components

Voroshilov

Buyvol

2021

MATEC Web Conf.

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“…As a basis for the optimization of road traffic, many researchers consider the study of the existing road network in combination with a preliminary analysis of the available statistics of road accidents and highlighting significant factors [12][13][14], the study of traffic intensity at a specific object, its modeling and optimization of traffic lights, changing the number of lanes, erecting barriers and road signs based on the study [15][16].…”

Section: Methodsmentioning

confidence: 99%

Search and Optimization of Factors to Improve Road Safety

Буйвол¹,

Iakupova²,

Makarova³

et al. 2020

International Journal of Engineering Research and Technology

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“…Another work was performed by [10] that investigated the significant contributing factors towards RTA risk and severity level for the case of Elabuga town using the data between 2017 and 2018. The attributes were divided into accident characteristics, driver information, vehicle conditions, road conditions, and environmental conditions.…”

Section: Related Workmentioning

confidence: 99%

Comparative analysis of regional variations in road traffic accident patterns with association rule mining

Chai,

Lau,

Tee

et al. 2023

EAI Endorsed Trans Perv Health Tech

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INTRODUCTION: Road Traffic Accidents (RTAs) patterns discovery is vital to formulate mitigation strategies based on the characteristics of RTAs.OBJECTIVES: Various studies have utilised Apriori algorithm for RTA pattern discovery. Hence, this work aimed to explore the applicability of FP-Growth algorithm to discover and compare the RTA patterns in several regions.METHODS: Orange data mining toolkit is used to discover RTA patterns from the open-access RTA datasets from Addis Ababa city (12,317 samples), Finland (371,213 samples), Berlin city-state (50,119 samples), New Zealand (776,878 samples), the UK (1,048,575 samples), and the US (173,829 samples).RESULTS: There are similarities and differences in RTA patterns among the six regions. The five common factors contributing to RTAs are road characteristics, type of road users or objects involved, environment, driver’s profile, and characteristics of RTA location. These findings could be beneficial for the authorities to formulate strategies to reduce the risk of RTAs.CONCLUSION: Discovery of RTA patterns in different regions is beneficial and future work is essential to discover the RTA patterns from different perspectives such as seasonal or periodical variations of RTA patterns.

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Association Rules to Identify Factors Affecting Risk and Severity of Road Accidents

Cited by 10 publications

References 0 publications

Application of intelligent analysis to identify defective vehicle components

Application of intelligent analysis to identify defective vehicle components

Search and Optimization of Factors to Improve Road Safety

Comparative analysis of regional variations in road traffic accident patterns with association rule mining

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