ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BATON ROUGE, LA · MARCH 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/march-2024-report
Monthly Traffic Safety Analysis
1,394 CRASHES IN
BATON ROUGE, LA
MARCH 2024
In March 2024, Baton Rouge recorded 1,394 vehicle crashes, a 3.9% increase from the 1,342 crashes documented in March 2023. This year-over-year rise was accompanied by an increase in total injuries from 1,035 to 1,088. A notable shift occurred in crashes under adverse weather conditions, with collisions during rain more than doubling from 49 to 107.
1,394
▲ 3.9%was 1,342
Total Crash Events
7
▲ 16.7%was 6
Fatal Crashes
1,088
▲ 5.1%was 1,035
Injury Crashes
331
▲ 6.4%was 311
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 · 2024-03-01 to 2024-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash trends in Baton Rouge show a year-over-year increase for the month of March. Total collisions rose by 3.9%, from 1,342 in March 2023 to 1,394 in March 2024. This increase was also reflected in crash outcomes, with total injuries rising by 5.1% and one additional fatality recorded compared to the same period last year.
331
Hit-and-Run Crashes — March 2024
▲ 6.4% vs prior (311)
Hit-and-run incidents increased in both count and rate in March 2024 compared to the previous year. The total number of hit-and-run crashes rose by 6.4%, from 311 to 331. The hit-and-run rate, representing the proportion of all crashes that were hit-and-runs, also trended upward, increasing from 23.2% in March 2023 to 23.7% in March 2024.
When Crashes Happen
The temporal patterns of crashes remained largely consistent year-over-year. Friday was the day with the most traffic collisions in both March 2024 (291 crashes) and March 2023 (269 crashes). While the overall daily distribution was similar, March 2024 saw higher crash volumes on most days of the week, particularly on Monday, which saw an increase from 165 to 198 crashes.
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-03-01 to 2024-03-31 · Crash date field aggregated by weekday
Crash Severity Breakdown
Crash severity saw a slight shift towards more severe outcomes in March 2024 compared to the prior year. The number of fatal crashes increased from 6 to 7, and the fatal crash rate rose from 0.45% to 0.50%. Similarly, the proportion of crashes resulting in injury increased from 77.1% to 78.0%, while the share of no-injury crashes decreased from 22.4% to 21.4%.
Outcome by Severity (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-03-01 to 2024-03-31 · 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 · 2024-03-01 to 2024-03-31 · Most severe injury per crash record
Top Contributing Factors
In both March 2023 and March 2024, 'Violations' was the leading contributing factor cited in crashes. The count of crashes attributed to violations remained stable, increasing slightly from 995 to 1,000, though its share of all factors decreased from 74.1% to 71.7%. The second-ranked factor, 'Movement prior to crash', saw a more significant increase in count, rising from 298 incidents to 334, a 12.1% increase.
Officer-Reported Primary Contributing Cause
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-03-01 to 2024-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
While clear weather and dry roads remained the most common conditions for crashes in both periods, March 2024 saw a significant increase in collisions during adverse weather. The number of crashes occurring in rain more than doubled, from 49 in March 2023 to 107 in March 2024. Correspondingly, crashes on wet road surfaces rose by 128%, from 78 to 178 incidents year-over-year.
Weather
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-03-01 to 2024-03-31 · Weather condition at time of crash
Lighting
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-03-01 to 2024-03-31 · Lighting condition field
Road Surface
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-03-01 to 2024-03-31 · 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: 2024-03-01 through 2024-03-31
- Report generated: June 19, 2026
Data Coverage
- Reporting period: 2024-03-01 through 2024-03-31 (31 days)
- Geographic scope: Baton Rouge, LA
- Total crash records analyzed: 1,394
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: March 2024." Published June 19, 2026. Reporting period: 2024-03-01 to 2024-03-31. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/march-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: 2024-03-01 – 2024-03-31
Generated: June 19, 2026 · All rights reserved