This repository offers code to reuse methodology and repeat experiments in the study "Learning Collision Risk Proactively from Naturalistic Driving at Scale".
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Updated
Mar 9, 2026 - Python
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
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
Script to convert non-public traffic accident data for Aichi Prefecture, Japan into Parquet format.
Final Exam Project for Database Administration 2 course. This project stores the traffic accident in current year using MongoDB with web interface.
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.
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.
Testing Machine Learning models to predict severity of traffic collisions.
Tools for Traffic Accident Data in Japan
Machine learning pipeline for predicting traffic accident severity using Logistic Regression and SVM (Linear, Polynomial, RBF) classifiers on road accident data with features like speed, weather, road condition, driving experience, junction type, and light conditions.
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.
Analysis of traffic congestion and car accidents data in the Kingdom of Saudi Arabia.
for academic paper(December 2025 to Febuary 2026)
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.
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