traffic-accidents

This repository offers code to reuse methodology and repeat experiments in the study "Learning Collision Risk Proactively from Naturalistic Driving at Scale".

An analysis of traffic accident data for the UK in 2014, using data from the UK Data Service. (Sourced from Kaggle with original data coming from UK Data Service. See wiki for complete citations.)

NSS Midcourse Project

🚘 웹 기반 교통사고 예측 사이트

🌍 Brazil Road Accidents

Анализ ДТП в России (2015–2024) с помощью Python, SQL и визуализаций

Analysis of traffic accidents causes per province in Saudi Arabia in 2017-2018. Original data fetched from Saudi Open Data Portal.

Análisis geoespacial de 5,779 siniestros viales en Teusaquillo (2015-2023) | Power BI + Excel

Análisis y visualización de siniestros viales en Bogotá (2015–2020) con Python, Pandas, Matplotlib y Seaborn. Incluye dashboard, análisis temporal, causas, localidades, vehículos y actores involucrados.

Looking at the fatality rates of traffic accidents in the US and which factors might impact these rates, leveraging several big data tools: AWS EMR cluster, HDFS, Hive, Spark, Hbase.

Road Risk Visualization Demo

Big data analysis of US traffic accidents using Polars, PySpark, Random Forest, Plotly, and Dash.

Tools for Traffic Accident Data in Japan

Testing Machine Learning models to predict severity of traffic collisions.

This project is a comprehensive machine learning project developed to analyze and predict traffic accidents in the United States. The project works with over 7.7 million accident data collected between 2016-2023 and provides an interactive web application for real-time predictions.

In-depth Excel-driven exploration of road accident statistics — analyzing severity levels, environmental factors, and temporal patterns through dynamic dashboards, performance metrics, and interactive visuals. Perfect for Excel analytics learners and professionals aiming to enhance data visualization and road safety analysis skills.

Central directory for localized city crash engines. Interconnecting custom regional safety mapping, road segment analytics, and accident exposure engines.

Script to convert non-public traffic accident data for Aichi Prefecture, Japan into Parquet format.

This project is a comprehensive machine learning project developed to analyze and predict traffic accidents in the United States. The project works with over 7.7 million accident data collected between 2016-2023 and provides an interactive web application for real-time predictions.

Final Exam Project for Database Administration 2 course. This project stores the traffic accident in current year using MongoDB with web interface.