The Road Accident Analysis project aims to uncover key insights and patterns from accident data using Tableau. This project provides a visual representation of accident trends, locations, causes, and other influencing factors to help stakeholders understand and address safety issues on roads.
- Analyze road accident data to identify trends and patterns.
- Visualize key metrics such as accident severity, frequency, and contributing factors.
- Provide actionable insights to improve road safety and reduce accidents.
The dataset used in this project includes the following attributes:
- Date and Time: Timestamp of the accident.
- Location: Geographic location of the accident.
- Weather Conditions: Weather at the time of the accident.
- Road Surface Conditions: Information on whether the road was wet, dry, or icy.
- Vehicle Types: Types of vehicles involved in the accidents.
- Casualties: Number of people injured or killed.
- Accident Severity: Classification of accidents based on the level of impact (e.g., slight, serious, fatal).
- Light Condition: Lighting conditions during the accident (e.g., daylight, night with streetlights).
- Number of Vehicles: Total vehicles involved in each accident.
- Road Type: Type of road where the accident occurred (e.g., single carriageway, dual carriageway,roundabout,one way street,slip road).
- Urban or Rural Area: Whether the accident took place in an urban or rural area.
- KPI and Area Chart: Displays the number of accidents, total casualties, fatal casualties, serious casualties, and slight casualties for the current and previous year.
- KPI for Casualties by Vehicle Type: Highlights the distribution of casualties based on the type of vehicle involved.
- Pie Chart for Casualties by Weather Type: Illustrates how weather conditions affect the number of casualties.
- Pie Chart for Casualties by Road Surface Type: Shows the distribution of casualties based on the type of road surface.
- Bar Chart for Casualties by Road Type: Visualizes casualties across different road types.
- Filters: Interactive filters for selecting the current year, previous year, and specific types of casualties.
- Tableau: For creating interactive dashboards and visualizations.
- Excel/CSV: For data preprocessing and cleaning before importing into Tableau.
- Data Collection: Gathered road accident data from reliable sources.
- Data Cleaning: Addressed missing values, standardized formats, and removed outliers.
- Data Visualization: Created dashboards in Tableau to highlight patterns and trends.
- Insights Generation: Derived key takeaways and recommendations based on visualizations.
- Handling incomplete or inconsistent data.
- Integrating multiple data sources into Tableau.
- Designing intuitive dashboards for diverse audiences.
- Incorporating real-time accident data for live monitoring.
- Expanding the dataset to include more regions and years.
- Using predictive analytics to forecast accident trends and identify potential high-risk areas.
This project demonstrates the power of Tableau in analyzing and visualizing complex datasets. The insights generated can help policymakers and safety organizations implement targeted interventions to enhance road safety.