Road Accident Analysis Using Power BI

Road traffic accidents remain one of the leading causes of death and injury worldwide. Understanding the factors that contribute to these accidents, analyzing patterns, and predicting accident severity are crucial in designing effective safety measures. This research explores various aspects of road accident analysis, including identifying contributing factors, predicting accident severity, and recommending improvements for road safety. Using machine learning models, traffic accident data is analyzed to uncover key insights. This paper presents a systematic analysis of road accident data, emphasizing the role of human factors, environmental conditions, vehicle characteristics, and road infrastructure in accident causation. Predictive models are developed to assess accident severity, and recommendations for safety measures are provided.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-18
DOI
https://doi.org/10.5281/zenodo.15239622
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Road Accident Analysis Using Power BI

Zenodo (CERN European Organization for Nuclear Research)
Traffic and Road Safety
article

Road Accident Analysis Using Power BI

article en

Abstract

Road traffic accidents remain one of the leading causes of death and injury worldwide. Understanding the factors that contribute to these accidents, analyzing patterns, and predicting accident severity are crucial in designing effective safety measures. This research explores various aspects of road accident analysis, including identifying contributing factors, predicting accident severity, and recommending improvements for road safety. Using machine learning models, traffic accident data is analyzed to uncover key insights. This paper presents a systematic analysis of road accident data, emphasizing the role of human factors, environmental conditions, vehicle characteristics, and road infrastructure in accident causation. Predictive models are developed to assess accident severity, and recommendations for safety measures are provided.

Zenodo (CERN European Organization for Nuclear Research)
Government Medical College (IN)
Openalex Percentile: Top 50%
Traffic and Road Safety
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.