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Data · dataset · 2025

Motorbike Accident Severity Analysis Dataset

Listed in Teesside University Research Data Repository

The dataset used in this study focuses on road traffic accidents involving motorcyclists in Bangladesh.

Description

It comprises various attributes related to the biker, road, environmental conditions, and accident outcomes. The dataset contains both categorical and numerical features, making it suitable for both classification and regression analysis.

Key features include: Biker Attributes: Biker_Age, Biker_Occupation, Biker_Education_Level, Riding_Experience, Daily_Travel_Distance, Talk_While_Riding, Smoke_While_Riding, Wearing_Helmet, Motorcycle_Ownership, Valid_Driving_License. Bike and Road Conditions: Bike_Condition, Road_Type, Road_condition, Weather, Time_of_Day, Traffic_Density, Speed_Limit, Bike_Speed, Number_of_Vehicles. Behavioral Factor: Biker_Alcohol.

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Target Variable: Accident_Severity (e.g., No Accident, Minor, Moderate, Severe). The dataset was collected through field surveys and interviews with accident victims and bystanders at various accident sites across Bangladesh. It reflects real-world scenarios and human behavior patterns associated with motorbike accidents, making it valuable for training machine learning models aimed at predicting accident severity and identifying contributing risk factors.

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Where it is published

Catalogue records · 1

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Provenance · 1 source records, 7 field assertions
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Teesside University Research Data Repositoryoai:data.mendeley.com/rm8t8kmhpj.35 h agoJSON v1
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concepts[field].anzsrc:field:490302mapping · researchdata tees ac ukvocabulary-mapper@1.0.0keywords['Numerical Analysis']
concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
descriptionsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/description
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