Spatial Analysis of Accident Spots Using Weighted Severity Index (WSI) and Density-Based Clustering Algorithm

Olusina, Jo; Ajanaku, WA

doi:10.4314/jasem.v21i2.22

Cited by 9 publications

(9 citation statements)

References 7 publications

(6 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The proposed method adopts the assumption taken to identify black spot from literature reviews: the site/area must have enough accidents to identify a pattern, the site/area must have enough accidents of the same type, and the accidents could be located on a map-based platform [7], [8].…”

Section: Methodological Proposalmentioning

confidence: 99%

“…Also, photographs of the accident spots and interviews with all stakeholders, such as e.g. police, road users, traffic officials, are helpful to ascertain the black spots [8].…”

Section: Methodological Stepsmentioning

confidence: 99%

“…Resampling: -given that the obtained three classes are highly imbalanced and to avoid a biased model, the proposed method suggests resampling via down sample majority classes to balance out the three classes [8]. fig.1) WSI is a scientific method that is used for identifying the accident blackspots [9], based on their priority value criterion or distribution of Blackspots Severity (BSS).…”

Section: Methodological Stepsmentioning

confidence: 99%

“…Where Wi = ∑ individual weight of factors/ road segment The road section with the highest value is less prone to accidents than the road section with a lower value [8]. The classification of the road section is done according to the values given in Table 2.…”

Section: Weight Severity Index Analysis (Step1-b and Step 2-e Inmentioning

confidence: 99%

See 3 more Smart Citations

A Mixed-Method Proposal for Traffic Hotspots Mapping in African Cities using Raw Satellite Imagery

Kebede¹

2020

IJERT

View full text Add to dashboard Cite

Road traffic fatalities disproportionately affect low-and middle-income countries. This research provides a method that helps cities in developing countries to use their limited resource to control accident-prone locations with satellite data insights. The proposed method is a mixed approach from both transport and the emerging machine learning discipline. In the first step, accident spots labeled using the Weighted Severity Index (WSI) with 14 risk factors that potentially influence the occurrence of an accident. Then, the computer is trained to look for blackspots using the labeled geoinformation data obtained from the WSI analysis. This cuttingedge method is called transfer learning with Convolutional Neural Networks (CNNs), which is the knowledge gained from previous training uses to identify a similar problem to a new location. The method is an inexpensive and reliable blackspot identifying solutions that extract data insights from freely available satellite imagery and open-source data.

show abstract

Section: Methodological Proposalmentioning

confidence: 99%

“…Also, photographs of the accident spots and interviews with all stakeholders, such as e.g. police, road users, traffic officials, are helpful to ascertain the black spots [8].…”

Section: Methodological Stepsmentioning

confidence: 99%

Section: Methodological Stepsmentioning

confidence: 99%

Section: Weight Severity Index Analysis (Step1-b and Step 2-e Inmentioning

confidence: 99%

See 2 more Smart Citations

A Mixed-Method Proposal for Traffic Hotspots Mapping in African Cities using Raw Satellite Imagery

Kebede¹

2020

IJERT

View full text Add to dashboard Cite

show abstract

“…The researcher should have a clear understanding of spatial and temporal incidents that caused the accident to undergo statistical mapping and modeling using unique data [45,46,47]. In this research, the software Arc GIS was used to analyze the accident spots.…”

Section: Spatial Accident Data Analysismentioning

confidence: 99%

Identifying Influencing Factors of Road Accidents in Emerging Road Accident Black spots<strong> </strong><strong> </strong>

Gheisari¹

2022

Preprint

View full text Add to dashboard Cite

This paper deals with identifying the accident black spots and the influencing factors causing accidents using factored analysis in the medium-sized city (Tirunelveli) in India. From the literature review, the geospatial technique to identify the black spots and the factors causing accidents was used for analysis. The most influencing factors driving the accident were identified and ranked based on the repetitive occurrence of accidents in the black spot area. The spearman ranking system obtained the correlation among the factors causing accidents. The factor analysis technique was utilized to identify the key factors driving the repetitive accidents and group them. This study will help transportation planners to understand the factors causing accidents and take appropriate measures to reduce the casualties in the road construction planning stage and existing conditions.

show abstract

Rapid-Response Framework for Defensive Driving Based on Internet of Vehicles Using Message-Oriented Middleware

2018

View full text Add to dashboard Cite

Spatial Analysis of Accident Spots Using Weighted Severity Index (WSI) and Density-Based Clustering Algorithm

Cited by 9 publications

References 7 publications

A Mixed-Method Proposal for Traffic Hotspots Mapping in African Cities using Raw Satellite Imagery

A Mixed-Method Proposal for Traffic Hotspots Mapping in African Cities using Raw Satellite Imagery

Identifying Influencing Factors of Road Accidents in Emerging Road Accident Black spots<strong> </strong><strong> </strong>

Rapid-Response Framework for Defensive Driving Based on Internet of Vehicles Using Message-Oriented Middleware

Contact Info

Product

Resources

About