Road crashes & traffic safety
Mapping road crashes: FARS and STATS19, fatal and injury collisions, rates per resident and per mile driven, pedestrians and cyclists, time of day and light, and the codes that hide missing values.
Road crash data comes in two great open forms: censuses of fatal crashes, such as the US Fatality Analysis Reporting System, and police records of injury collisions, such as Great Britain’s STATS19, alongside city crash datasets like Chicago’s. The guides here map them, compute rates per resident and per mile driven, find the streets where most people are killed or seriously injured, and look at pedestrians, light, time and speed.
Every number comes from a run on the published files. FARS 2023 records 41,025 deaths, 1.26 per 100 million vehicle miles; STATS19’s serious injury counts need the Department for Transport’s adjustment before police forces can be compared; and coded missing values, such as a latitude of 77.7777, look like real data until they are filtered.
🧭 Start with the concepts
The ideas the how-to guides below assume you already have.
⚙️ Then do the task
Step-by-step walkthroughs with code you can copy and adapt.
- How to Map Fatal Road Crashes in the US with FARS in Python
- How to Map UK Road Collisions from STATS19 in Python
- How to Build a High-Injury Network from Crash Data in Python
- How to Analyse Pedestrian Deaths with FARS in Python
- How to Calculate Road Death Rates per Vehicle Mile in Python
- How to Estimate Alcohol-Impaired Road Deaths with FARS in Python
Show every how-to guide in this topic
- How to Analyse Cyclist Casualties from STATS19 in Python
- How to Measure the Effect of the Clock Change on Road Crashes in Python
- How to Find Clusters of Fatal Crashes with DBSCAN in Python
- How to Analyse Road Death Trends with FARS in Python
- How to Analyse Speeding-Related Crashes with FARS in Python
- How to Map Road Casualty Rates by Local Authority in Python
- How to Calculate Road Collision Rates per Vehicle-Kilometre
🔧 When it breaks
The errors this topic produces, with the cause explained rather than just the command.
Related topics
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