ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BATON ROUGE, LA · FEBRUARY 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/february-2024-report
Monthly Traffic Safety Analysis
1,232 CRASHES IN
BATON ROUGE, LA
FEBRUARY 2024
In February 2024, Baton Rouge recorded 1,232 total vehicle crashes, a 6.2% increase from the 1,160 crashes reported in February 2023. While total crashes and injuries rose, the most significant year-over-year change was a sharp decline in traffic fatalities, which fell from 7 to 2.
1,232
▲ 6.2%was 1,160
Total Crash Events
2
▼ -71.4%was 7
Fatal Crashes
958
▲ 10.5%was 867
Injury Crashes
262
▼ -5.8%was 278
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 · 2024-02-01 to 2024-02-29 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends were mixed in the year-over-year comparison for February. The total number of crashes increased by 6.2%, rising from 1,160 to 1,232. Similarly, the number of injuries grew by 10.5% from 867 to 958. In contrast, fatalities saw a substantial decrease, dropping 71.4% from 7 in February 2023 to 2 in February 2024.
262
Hit-and-Run Crashes — February 2024
▼ -5.8% vs prior (278)
Hit-and-run incidents decreased in both count and as a percentage of total crashes. The number of hit-and-run crashes fell from 278 in February 2023 to 262 in February 2024, a 5.8% reduction. The hit-and-run rate also trended downward, declining from 24.0% of all crashes in the prior period to 21.3% in the current period.
When Crashes Happen
The temporal patterns of crashes remained largely consistent between February 2023 and February 2024. Thursday was the peak day for crashes in both periods, with the count increasing from 200 to 215 year-over-year. The top three days for crashes in 2024 were Thursday (215), Friday (207), and Wednesday (190), a slight shift from 2023's top days of Thursday (200), Friday (181), and Tuesday (175).
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-02-01 to 2024-02-29 · Crash date field aggregated by weekday
Crash Severity Breakdown
While total crashes increased, their severity profile shifted. The number of fatal crashes dropped from 7 to 2, and the fatality rate decreased from 0.6% to 0.16% of all crashes. Conversely, the proportion of crashes resulting in an injury increased, rising from 74.7% in February 2023 (867 incidents) to 77.8% in February 2024 (958 incidents). The share of non-injury crashes correspondingly decreased from 24.7% to 22.1%.
Outcome by Severity (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-02-01 to 2024-02-29 · 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 · 2024-02-01 to 2024-02-29 · Most severe injury per crash record
Top Contributing Factors
Driver violations remained the leading contributing factor in both periods, accounting for 910 crashes in February 2024 compared to 847 in February 2023. This represents a 7.4% increase in the count of violation-related crashes, while its share of all factors held steady at approximately 73-74%. The second-ranked factor, 'Movement prior to crash,' also saw a slight increase in count from 262 to 266 incidents. The top two contributing factors did not change in rank year-over-year.
Officer-Reported Primary Contributing Cause
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-02-01 to 2024-02-29 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Year-over-year data indicates a shift toward more crashes occurring in ideal conditions. Crashes on dry road surfaces increased from 996 to 1,138, and their share of total crashes rose from 85.9% to 92.4%. Similarly, crashes in clear weather grew from 940 to 1,088. Correspondingly, crashes during adverse conditions decreased, with incidents on wet roads falling from 140 to 69 and crashes in the rain dropping from 100 to 52.
Weather
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-02-01 to 2024-02-29 · Weather condition at time of crash
Lighting
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-02-01 to 2024-02-29 · Lighting condition field
Road Surface
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-02-01 to 2024-02-29 · 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: 2024-02-01 through 2024-02-29
- Report generated: June 19, 2026
Data Coverage
- Reporting period: 2024-02-01 through 2024-02-29 (29 days)
- Geographic scope: Baton Rouge, LA
- Total crash records analyzed: 1,232
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: February 2024." Published June 19, 2026. Reporting period: 2024-02-01 to 2024-02-29. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/february-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: 2024-02-01 – 2024-02-29
Generated: June 19, 2026 · All rights reserved