Hazardous-Driving-Spots-Around-the-World
OpenML dataset with id 43372
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/22102197/Hazardous-Driving-Spots-Around-the-World.arff
Upload date: 23 March 2022
Copyright license: No records found.
Dataset Characteristics
Number of features: 18 (numeric: 9, symbolic: 0 and in total binary: 0 )
Number of instances: 10,939
Number of instances with missing values: 4,085
Number of missing values: 6,089
Content This dataset identifies hazardous areas for driving according to harsh braking and accident level events within a specific area. Each month a new set of dangerous driving areas is produced and encapsulates one year of rolling data (i.e. from the previous month back 1 year). Associated with each area is a severity score that is based on the frequency of occurrences in the area and the severity of said occurrences. Data is aggregated over the previous 12 months. Data Some variables to point out:
SeverityScore: Severity score for each area as the number of harsh braking incidents and accident-level incidents for every 100 units of traffic flow. Traffic flow is defined as total hourly vehicle volume in the geohash. IncidentsTotal: The total number of harsh braking incidents and accident-level events that have occurred within the geohash
Acknowledgements This dataset is aggregated over the previous 12 months and is updated monthly. This data is publicly available from Geotab (geotab.com). Inspiration As some inspiration, here are some questions:
Which countries have the highest number of hazardous spots? Least number?
Can you create a dynamic geospatial visualization?
This page was built for dataset: Hazardous-Driving-Spots-Around-the-World
