The project aims to analyze road accident data to identify trends and insights related to accidents and casualties. The analysis focused on key performance indicators measuring accident severity, vehicle type, road type and other factors. The primary goal is to help transportation authorities, law enforcement agencies and stakeholders improve traffic safety and reduce the number of casualties resulting from road accidents.
https://www.kaggle.com/datasets/richeeee/accident-data/data
Activities Carried Out
- Obtained the dataset.
- Identified stakeholders and their specific requirements related to the KPIs.
- Examined the raw data to understand its structure and content.
- Imported the data into Power BI for analysis.
- Performed data cleaning to handle missing values, duplicates and inconsistencies.
- Prepared the data for analysis.
- Developed a variety of charts and visualizations to represent insights effectively.
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Accident Overview: In the 2021-22 period, the United Kingdom experienced a total of 307,970 road accidents, resulting in 418,000 casualties.
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High-Accident Districts: Birmingham emerged as the district with the highest number of accidents, recording 6,200 incidents, signifying the need for focused safety measures in this area.
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Severity Distribution: The majority of accidents fall into the "slight" severity category, with the highest casualty count. Notably, approximately 40,000 accidents were classified as "severe," indicating the need for heightened attention to reduce their impact.
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Monthly Patterns: The months of October and November stood out with the highest growth in accidents and casualties, suggesting a seasonal factor that authorities should consider when planning safety measures.
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Urban Accident Concentration: Urban areas were the predominant locations for accidents, accounting for 64.46% of all incidents. This highlights the importance of urban safety planning and infrastructure improvements.
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Day of the Week Analysis: Fridays emerged as the day with the highest number of accidents, warranting additional vigilance and enforcement measures on this day to curb accidents.
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Weather and Light Impact: A significant proportion of accidents occurred under favorable weather conditions with no high winds, often during daylight hours. This underscores the need for drivers to remain cautious even in seemingly ideal conditions and emphasizes the importance of factors beyond weather and light.
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Vehicle Types Involved: The majority of accidents involved cars, with approximately 240,000 car-related accidents. This insight underscores the need for targeted education and awareness campaigns for car drivers.
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Road Conditions and Junction Types: Dry road conditions were prevalent in all accidents analyzed, and accidents were less likely to occur near junctions. This finding suggests that road surface conditions and junction designs might not be significant contributors to accidents, emphasizing the need for investigating other factors contributing to road safety.
These insights provide a comprehensive understanding of the road accident landscape in the UK and serve as valuable input for developing strategies and interventions to enhance road safety and reduce casualties.
This project successfully analyzed UK road accident data and provided valuable insights into accidents and casualty trends. The visualizations and charts created in Power BI will assist transportation authorities and law enforcement agencies in making informed decisions to improve road safety. By focusing on high-risk areas, accident severity, and other key factors, stakeholders can implement targeted interventions to reduce casualties caused by road accidents.
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