Monthly Traffic Safety Analysis

1,108 CRASHES IN
BATON ROUGE, LA
MAY 2026

All metrics benchmarked againstMay 2025

In May 2026, Baton Rouge recorded 1,108 vehicle crashes, a 14.4% decrease from the 1,295 crashes documented in May 2025. This year-over-year decline was accompanied by a significant reduction in crash severity. The most notable shift was the complete elimination of traffic fatalities, which dropped from five in the prior year's period to zero in the current period.

1,108

▼ -14.4%was 1,295

Total Crash Events

0

▼ -100.0%was 5

Fatal Crashes

858

▼ -15.6%was 1,017

Injury Crashes

258

▼ -4.4%was 270

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 · 2026-05-01 to 2026-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety metrics in Baton Rouge showed a significant downward trend in May 2026 compared to the same month in the previous year. Total crashes fell by 14.4% (from 1,295 to 1,108), and the number of injuries decreased by 15.6% (from 1,017 to 858). Concurrently, total fatalities fell from five to zero.

258

Hit-and-Run Crashes — May 2026

▼ -4.4% vs prior (270)

The total number of hit-and-run crashes saw a slight decrease from 270 in May 2025 to 258 in May 2026. However, the hit-and-run rate, which measures these incidents as a percentage of total crashes, trended upward. The rate increased from 20.8% in the prior year period to 23.3% in the current period.

When Crashes Happen

Friday was the most frequent day for crashes in both May 2026 (218 crashes) and May 2025 (275 crashes), indicating a consistent weekly pattern. While the peak day did not change, crash counts decreased on most days of the week compared to the prior year. The second-busiest day shifted from Thursday in 2025 to Tuesday in 2026. Data was insufficient to compare crash patterns by hour.

Source: Baton Rouge Crash Data · Socrata Open Data · 2026-05-01 to 2026-05-31 · Crash date field aggregated by weekday

Crash Severity Breakdown

Crash severity decreased notably in May 2026 compared to the prior year. There were zero fatal crashes, down from five fatal incidents in May 2025. The number of injury-related crashes also fell from 1,017 to 858. As a proportion of all collisions, injury crashes saw a slight decline, accounting for 77.4% of incidents compared to 78.5% in the previous year.

Outcome by Severity (Crash Events)

Injury858minor injury crashes77.4%
↓-15.6%prior 1,017
No Injury250no injury crashes22.6%
↓-8.4%prior 273

Source: Baton Rouge Crash Data · Socrata Open Data · 2026-05-01 to 2026-05-31 · 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 · 2026-05-01 to 2026-05-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors remained consistent year-over-year, though their counts changed. 'Violations' was the top factor in both periods, but its crash count decreased by 17.6%, from 1,016 incidents in May 2025 to 837 in May 2026. In contrast, crashes attributed to 'Driver condition' increased in count by 22.2% (from 18 to 22), despite the overall reduction in total crashes.

Officer-Reported Primary Contributing Cause

Violations837 (75.5%)↓-17.6%prior 1,016
Movement prior to crash226 (20.4%)↓-3.0%prior 233
Driver condition22 (2%)↑22.2%prior 18
Roadway condition9 (0.8%)
Road surface4 (0.4%)
Vision obstructions3 (0.3%)↓-62.5%prior 8
Vehicle condition3 (0.3%)↓-57.1%prior 7
Non-motorist action2 (0.2%)
Weather condition1 (0.1%)
Traffic control1 (0.1%)

Source: Baton Rouge Crash Data · Socrata Open Data · 2026-05-01 to 2026-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Compared to the prior year, a larger proportion of crashes in May 2026 occurred during adverse conditions. The share of crashes on wet road surfaces nearly doubled, increasing from 12.0% of all incidents in May 2025 to 23.0% in May 2026. Similarly, the proportion of crashes occurring in rainy weather rose from 8.8% to 15.9% of the total.

Weather

Clear806 (73.5%)
↓-24.6%prior 1,069
Rain176 (16.1%)
↑54.4%prior 114
Cloudy114 (10.4%)
↑12.9%prior 101

Source: Baton Rouge Crash Data · Socrata Open Data · 2026-05-01 to 2026-05-31 · Weather condition at time of crash

Lighting

Daylight869 (79.3%)
↓-15.4%prior 1,027
Dark - continuous street lights164 (15.0%)
↓-10.4%prior 183
Dark - street lights at intersection only24 (2.2%)
↓-31.4%prior 35
Dawn/dusk18 (1.6%)
↓-10.0%prior 20
Dark - unknown lighting12 (1.1%)
↑100.0%prior 6
Dark - not lighted9 (0.8%)
↓-25.0%prior 12

Source: Baton Rouge Crash Data · Socrata Open Data · 2026-05-01 to 2026-05-31 · Lighting condition field

Road Surface

Dry829 (75.6%)
↓-26.2%prior 1,123
Wet255 (23.3%)
↑63.5%prior 156
Water (standing, moving)11 (1.0%)
Other1 (0.1%)

Source: Baton Rouge Crash Data · Socrata Open Data · 2026-05-01 to 2026-05-31 · 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: 2026-05-01 through 2026-05-31
  • Report generated: June 19, 2026

Data Coverage

  • Reporting period: 2026-05-01 through 2026-05-31 (31 days)
  • Geographic scope: Baton Rouge, LA
  • Total crash records analyzed: 1,108

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 2026." Published June 19, 2026. Reporting period: 2026-05-01 to 2026-05-31. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/may-2026-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

Baton Rouge, LA Crash Report — May 2026 | ThatCarHitMe.com