ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BATON ROUGE, LA · JANUARY 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/january-2024-report
Monthly Traffic Safety Analysis
1,101 CRASHES IN
BATON ROUGE, LA
JANUARY 2024
In January 2024, Baton Rouge recorded 1,101 traffic collisions, a 4.5% decrease from the 1,153 collisions reported in January 2023. While overall crash volume saw a modest decline, the most significant change was a sharp reduction in traffic fatalities, which fell from 6 in the prior year's period to 1.
1,101
▼ -4.5%was 1,153
Total Crash Events
1
▼ -83.3%was 6
Fatal Crashes
868
▼ -2.7%was 892
Injury Crashes
233
▼ -19.1%was 288
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 · 2024-01-01 to 2024-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends in Baton Rouge showed improvement in January 2024 compared to the same month in the prior year. Total crashes fell by 4.5%, from 1,153 to 1,101. This downward trend extended to crash outcomes, with total injuries decreasing from 892 to 868 and fatalities dropping from 6 to 1.
233
Hit-and-Run Crashes — January 2024
▼ -19.1% vs prior (288)
Hit-and-run incidents decreased in both volume and as a percentage of total crashes in January 2024 compared to the previous year. The number of hit-and-run crashes fell from 288 to 233, a 19.1% reduction in count. Correspondingly, the hit-and-run rate declined from 25.0% of all crashes in January 2023 to 21.2% in January 2024, indicating a downward trend.
When Crashes Happen
The temporal pattern of crashes showed some consistency and some shifts year-over-year. Tuesday remained the peak day for collisions in both January 2024 (201 crashes) and January 2023 (204 crashes). However, weekend crashes saw a notable decline, with the combined count for Saturday and Sunday falling from 271 in 2023 to 220 in 2024.
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-01-01 to 2024-01-31 · Crash date field aggregated by weekday
Crash Severity Breakdown
Crash severity improved significantly in January 2024 compared to the previous year. The number of fatal crashes dropped from 6 to 1, and the corresponding fatal crash share fell from 0.5% to 0.1% of all collisions. While the total number of injuries decreased from 892 to 868, the proportion of crashes involving an injury rose slightly from 77.4% to 78.8%.
Outcome by Severity (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-01-01 to 2024-01-31 · 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 · 2024-01-01 to 2024-01-31 · Most severe injury per crash record
Top Contributing Factors
The primary contributing factors cited in crashes remained consistent between January 2023 and January 2024, with 'Violations' being the most common factor in both periods. The count of crashes attributed to violations decreased from 833 to 803. Similarly, 'Movement prior to crash,' the second-ranked factor, saw its associated crash count drop from 257 to 233. The top three factors maintained their rank order year-over-year, with all experiencing a decrease in the number of associated crashes.
Officer-Reported Primary Contributing Cause
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-01-01 to 2024-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Environmental conditions during crashes shifted between the two periods, with a higher proportion of incidents occurring in adverse weather in January 2024. Crashes in rainy conditions increased from 86 to 135, and 14 crashes occurred during freezing rain, a condition not recorded in the prior year's period. This is reflected in road surface data, where crashes on wet surfaces rose from 154 to 219. The proportion of crashes occurring in darkness also increased, from 29.6% in January 2023 to 33.1% in January 2024.
Weather
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-01-01 to 2024-01-31 · Weather condition at time of crash
Lighting
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-01-01 to 2024-01-31 · Lighting condition field
Road Surface
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-01-01 to 2024-01-31 · 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: 2024-01-01 through 2024-01-31
- Report generated: June 19, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-01-31 (31 days)
- Geographic scope: Baton Rouge, LA
- Total crash records analyzed: 1,101
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: January 2024." Published June 19, 2026. Reporting period: 2024-01-01 to 2024-01-31. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/january-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: 2024-01-01 – 2024-01-31
Generated: June 19, 2026 · All rights reserved