ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BATON ROUGE, LA · JUNE 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/june-2024-report
Monthly Traffic Safety Analysis
1,065 CRASHES IN
BATON ROUGE, LA
JUNE 2024
In June 2024, Baton Rouge recorded 1,065 total traffic crashes, a 6.1% decrease from the 1,134 crashes reported in June 2023. Despite the overall reduction in collisions, the number of fatalities doubled, increasing from 2 in the prior year period to 4 in the current period.
1,065
▼ -6.1%was 1,134
Total Crash Events
4
▲ 100.0%was 2
Fatal Crashes
819
▼ -4.7%was 859
Injury Crashes
216
▼ -18.5%was 265
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 · 2024-06-01 to 2024-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the total number of crashes in Baton Rouge saw a year-over-year decline in June, falling by 6.1% from 1,134 to 1,065. This downward trend was also reflected in total injuries, which decreased by 4.7% from 859 to 819. In contrast, the number of fatalities rose from 2 to 4 during the same period.
216
Hit-and-Run Crashes — June 2024
▼ -18.5% vs prior (265)
Hit-and-run incidents decreased in both count and rate year-over-year. The number of hit-and-run crashes fell by 18.5%, from 265 in June 2023 to 216 in June 2024. The hit-and-run rate, representing the proportion of all crashes that were hit-and-runs, also trended downward, declining from 23.4% to 20.3%.
When Crashes Happen
The temporal pattern of crashes showed some consistency year-over-year, with Thursday remaining the peak day for collisions in both June 2024 and June 2023. However, the number of crashes on the peak day decreased from 224 in the prior year to 178 in the current period. Crashes on Friday also saw a notable decrease, falling from 211 to 153.
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-06-01 to 2024-06-30 · Crash date field aggregated by weekday
Crash Severity Breakdown
While total crashes decreased, the severity of crashes increased in June 2024 compared to the prior year. The proportion of crashes resulting in a fatality doubled from 0.2% to 0.4% of all incidents. Similarly, the share of crashes involving an injury rose slightly from 75.7% to 76.9%, while the proportion of no-injury crashes declined from 24.1% to 22.7%.
Outcome by Severity (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-06-01 to 2024-06-30 · 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 · 2024-06-01 to 2024-06-30 · Most severe injury per crash record
Top Contributing Factors
The primary contributing factors cited in crashes remained consistent year-over-year, with 'Violations' being the most common factor in both periods. The count of crashes attributed to 'Violations' decreased by 7.4%, from 850 in June 2023 to 787 in June 2024. The second-leading factor, 'Movement prior to crash,' saw a slight increase in count from 230 to 235 incidents.
Officer-Reported Primary Contributing Cause
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-06-01 to 2024-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both periods occurred in clear weather on dry roads during daylight hours. However, June 2024 saw a higher proportion of crashes under adverse conditions compared to the previous year. Crashes on wet roads increased by 32.3% from 65 to 86 incidents, and those occurring in the rain rose from 40 to 49. Similarly, while most collisions happened in daylight, the count of crashes in dark but lighted conditions increased from 130 to 134.
Weather
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-06-01 to 2024-06-30 · Weather condition at time of crash
Lighting
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-06-01 to 2024-06-30 · Lighting condition field
Road Surface
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-06-01 to 2024-06-30 · 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: 2024-06-01 through 2024-06-30
- Report generated: June 19, 2026
Data Coverage
- Reporting period: 2024-06-01 through 2024-06-30 (30 days)
- Geographic scope: Baton Rouge, LA
- Total crash records analyzed: 1,065
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: June 2024." Published June 19, 2026. Reporting period: 2024-06-01 to 2024-06-30. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/june-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: 2024-06-01 – 2024-06-30
Generated: June 19, 2026 · All rights reserved