ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BATON ROUGE, LA · MAY 2024
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/louisiana/baton-rouge/may-2024-report
Monthly Traffic Safety Analysis
1,339 CRASHES IN
BATON ROUGE, LA
MAY 2024
In May 2024, Baton Rouge recorded 1,339 vehicle crashes, an increase from the 1,245 crashes reported in May 2023. This represents a 7.6% year-over-year rise in total collisions. The most significant change was in crash severity, with the number of fatalities doubling from 2 to 4 and total injuries increasing from 963 to 1,029.
1,339
▲ 7.6%was 1,245
Total Crash Events
4
▲ 100.0%was 2
Fatal Crashes
1,029
▲ 6.9%was 963
Injury Crashes
319
▲ 4.6%was 305
Hit-and-Run Crashes
Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons.
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-05-01 to 2024-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Baton Rouge show an increase in May 2024 compared to the same month in the prior year. Total crashes rose by 7.6% from 1,245 to 1,339, while total injuries increased by 6.9% from 963 to 1,029. Fatalities also increased, doubling from 2 in May 2023 to 4 in May 2024.
319
Hit-and-Run Crashes — May 2024
▲ 4.6% vs prior (305)
The absolute number of hit-and-run incidents increased from 305 in May 2023 to 319 in May 2024, a 4.6% rise in count. Despite this increase in volume, the hit-and-run rate as a percentage of all crashes slightly decreased, moving from 24.5% in the prior year to 23.8% in the current period. This indicates that hit-and-run crashes grew at a slower rate than total crashes.
When Crashes Happen
The temporal pattern of crashes shifted between the two periods, with the peak day for collisions moving from Tuesday in May 2023 (227 crashes) to Friday in May 2024 (272 crashes). Fridays saw a substantial year-over-year increase in incidents, rising from 189 to 272, while crashes on Tuesdays decreased from 227 to 173. Data on crash times by hour was not available for comparison in either period.
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-05-01 to 2024-05-31 · Crash date field aggregated by weekday
Crash Severity Breakdown
The severity of crashes increased in May 2024, with the number of fatal crashes doubling from 2 to 4 compared to May 2023. Consequently, the fatal crash rate rose from 0.16% to 0.3% of all collisions. While the proportion of crashes resulting in injury remained relatively stable, decreasing slightly from 77.3% to 76.8% of the total, the absolute number of injury-related crashes grew from 963 to 1,029.
Outcome by Severity (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-05-01 to 2024-05-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)
Severity Distribution (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-05-01 to 2024-05-31 · Most severe injury per crash record
Top Contributing Factors
Violations remained the top contributing factor in both periods, with the count of such crashes increasing by 5.3% from 961 in May 2023 to 1,012 in May 2024. The second-ranked factor, 'Movement prior to crash,' saw a 16% increase in count from 244 to 283 incidents. Crashes attributed to 'Driver condition' also grew, with the count rising by 50% from 16 to 24, though the top three factor rankings remained unchanged.
Officer-Reported Primary Contributing Cause
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-05-01 to 2024-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
While most crashes in both periods occurred in clear weather, May 2024 saw a notable increase in crashes under adverse conditions. The number of crashes during rain increased by 176% from 42 to 116, and collisions on wet road surfaces rose by 118% from 71 to 155. In terms of lighting, crashes in darkness with continuous street lights increased from 147 to 193 year-over-year.
Weather
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-05-01 to 2024-05-31 · Weather condition at time of crash
Lighting
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-05-01 to 2024-05-31 · Lighting condition field
Road Surface
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-05-01 to 2024-05-31 · Road surface condition field
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Baton Rouge Crash Data, accessed programmatically via the Socrata Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.
Data Retrieval
- Access method: Socrata Open Data API (SoQL queries)
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2024-05-01 through 2024-05-31
- Report generated: June 19, 2026
Data Coverage
- Reporting period: 2024-05-01 through 2024-05-31 (31 days)
- Geographic scope: Baton Rouge, LA
- Total crash records analyzed: 1,339
Analytical Methodology
- Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
- Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
- Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
- Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
- Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
- Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
- AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.
Limitations & Disclaimers
- Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
- Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
- Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
- AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
- Percentages are calculated from reported data and are subject to rounding.
Non-Affiliation Disclosure
This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.
Data License
The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.
Corrections & Feedback
If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.
Suggested Citation
ThatCarHitMe.com (Injuria.ai). "Baton Rouge, LA Crash Intelligence Report: May 2024." Published June 19, 2026. Reporting period: 2024-05-01 to 2024-05-31. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/may-2024-report
About the Publisher
ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.
Questions about this report's data or methodology: data@injuria.ai
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Baton Rouge Crash Data · Socrata
Period: 2024-05-01 – 2024-05-31
Generated: June 19, 2026 · All rights reserved