ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · MARCH 2026
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/maryland/statewide/march-2026-report
Monthly Traffic Safety Analysis
794 CRASHES IN
MONTGOMERY, MD
MARCH 2026
In March 2026, Montgomery County recorded 794 total crashes, a figure nearly identical to the 795 crashes reported in March 2025. Despite the stability in overall crash volume, the number of fatalities doubled from 2 to 4 year-over-year. This increase in fatalities occurred across 5 fatal crashes in the current period, up from 2 fatal crashes in the prior year.
794
▼ -0.1%was 795
Total Crash Events
4
▲ 100.0%was 2
Persons Killed
279
▲ 2.2%was 273
Persons Injured
20
▼ -4.8%was 21
Hit-and-Run Crashes
Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 41 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-03-01 to 2026-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash totals in Montgomery County remained stable, decreasing by a single incident from 795 in March 2025 to 794 in March 2026. However, the severity of collisions trended upwards, as total injuries increased from 273 to 279 and fatalities doubled from 2 to 4. This indicates a shift towards more severe outcomes despite a consistent number of total crashes.
20
Hit-and-Run Crashes — March 2026
▼ -4.8% vs prior (21)
The frequency of hit-and-run crashes remained stable year-over-year. In March 2026, there were 20 hit-and-run incidents recorded, accounting for a rate of 2.5% of all crashes. This is a marginal decrease from March 2025, which saw 21 hit-and-run crashes at a rate of 2.6%.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
42
Pedestrians Injured
12
Cyclists Injured
223
Motorists Injured
2
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-03-01 to 2026-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed shifts between the two periods. The peak day for collisions moved from Monday (146 crashes) in March 2025 to Tuesday (144 crashes) in March 2026. Similarly, the daily peak hour for crashes shifted slightly later, from the 3 PM hour in the prior year to the 4 PM hour in the current year.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-03-01 to 2026-03-31 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-03-01 to 2026-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased in March 2026 compared to the previous year, with the number of fatalities rising from 2 to 4. The fatal crash rate more than doubled, increasing from 0.25% to 0.63% of all crashes. While the count of serious injury crashes decreased from 20 to 17, crashes resulting in minor or possible injuries increased, leading to a higher total injury count of 279 versus 273 in the prior year.
Severity is per crash event (most severe injury). 5 fatal crash events resulted in 4 persons killed.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-03-01 to 2026-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-03-01 to 2026-03-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor in both periods was 'Failed to Yield Right-of-Way,' though its count decreased from 66 crashes in March 2025 to 52 in March 2026. The count for 'Followed Too Closely' also declined from 31 to 26. Conversely, crashes attributed to 'Operated Motor Vehicle in Inattentive, Careless, Negligent, or Erratic Manner' increased from 12 to 15 incidents, and collisions where 'Too Fast For Conditions' was a factor rose from 10 to 13.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-03-01 to 2026-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
A notable shift occurred in the conditions under which crashes happened, with a higher number of incidents taking place in adverse weather in March 2026. Crashes during rain increased from 40 to 98, and those on wet road surfaces rose from 50 to 167. Consequently, the share of crashes occurring on dry roads decreased from 80% in the prior year to 63.5% in the current year. Lighting conditions for crashes remained broadly similar across both periods.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-03-01 to 2026-03-31 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-03-01 to 2026-03-31 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-03-01 to 2026-03-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained consistent, with Toyota, Honda, and Ford leading in both periods, although all three saw a slight decrease in crash involvement counts. An analysis of vehicle types shows an increase in Sport Utility Vehicle involvement from 217 to 232 and a rise in Transit Bus involvement from 23 to 37. Conversely, the number of Passenger Cars in crashes decreased from 919 to 881.
Top Vehicle Makes (1,360 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-03-01 to 2026-03-31 · Vehicle unit records
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Montgomery County Crash Reporting (ACRS) (https://data.montgomerycountymd.gov/d/bhju-22kf), 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)
- Dataset URL: https://data.montgomerycountymd.gov/d/bhju-22kf
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2026-03-01 through 2026-03-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2026-03-01 through 2026-03-31 (31 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 794
- Total persons involved: 1,419
- Total vehicles involved: 1,360
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). "montgomery, MD Crash Intelligence Report: March 2026." Published September 9, 2026. Reporting period: 2026-03-01 to 2026-03-31. Data source: Montgomery County Crash Reporting (ACRS), Socrata Open Data. Dataset: https://data.montgomerycountymd.gov/d/bhju-22kf. Available at: https://thatcarhitme.com/crash-data/maryland/statewide/march-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
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Montgomery County Crash Reporting (ACRS) · Socrata
Period: 2026-03-01 – 2026-03-31
Generated: September 9, 2026 · All rights reserved