ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · DECEMBER 2025
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/december-2025-report
Monthly Traffic Safety Analysis
875 CRASHES IN
MONTGOMERY, MD
DECEMBER 2025
In December 2025, Montgomery County recorded 875 total crashes, a slight increase of 0.5% from the 871 crashes documented in December 2024. While the overall crash volume remained stable, the number of resulting fatalities rose from one to three year-over-year. Concurrently, the total number of individuals injured in these crashes decreased by 16.4%, from 304 to 254.
875
▲ 0.5%was 871
Total Crash Events
3
▲ 200.0%was 1
Persons Killed
254
▼ -16.4%was 304
Persons Injured
13
▼ -43.5%was 23
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 45 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-12-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year, the total number of crashes in Montgomery County remained relatively stable, increasing by just 0.5% from 871 in December 2024 to 875 in December 2025. However, the outcomes of these crashes shifted, as total reported injuries decreased by 16.4% while total fatalities increased from one to three.
13
Hit-and-Run Crashes — December 2025
▼ -43.5% vs prior (23)
Hit-and-run incidents decreased significantly in December 2025 compared to the same month in 2024. The total count of hit-and-run crashes fell by 43.5%, from 23 to 13. This downward trend is also reflected in the hit-and-run rate, which dropped from 2.6% of all crashes in the prior period to 1.5% in the current period.
Vulnerable Road User Casualties
1
Pedestrians Killed
1
Cyclists Killed
1
Motorists Killed
0
Other Killed
39
Pedestrians Injured
5
Cyclists Injured
206
Motorists Injured
4
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-12-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes showed some year-over-year changes. Tuesday remained the peak day for crashes in both periods, though the count on Tuesdays increased from 144 to 166. The daily peak hour for collisions shifted one hour earlier, moving from 6 PM in the prior period (70 crashes) to 5 PM in the current period (77 crashes).
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-12-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-12-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity outcomes shifted between the two periods. The number of fatal crashes increased from one in December 2024 to three in December 2025. Conversely, crashes resulting in any form of injury (serious, minor, or possible) decreased in both count and proportion, with serious injury crashes falling from 21 to 13. Crashes with no reported injuries increased from 573 (65.8% of total) to 609 (69.6% of total).
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-12-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-12-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent, with 'Failed to Yield Right-of-Way' being the top cause in both December 2024 (59 crashes) and December 2025 (74 crashes), a 25.4% increase in count. Crashes where 'Too Fast For Conditions' was a factor more than doubled, rising from 13 to 27 incidents, which represents a 107.7% increase in count. In contrast, incidents citing 'Operated Motor Vehicle in Inattentive, Careless, Negligent, or Erratic Manner' decreased from 19 to 8.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-12-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
A higher proportion of crashes in December 2025 occurred in favorable conditions compared to the previous year. Crashes in clear weather increased from 608 to 681, while those in rain decreased from 129 to 47. Similarly, incidents on dry road surfaces rose from 528 to 607, and crashes on wet surfaces fell from 214 to 89. The distribution of crashes by lighting condition remained largely consistent, with daylight crashes being the most frequent in both periods.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-12-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-12-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-12-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The makes and types of vehicles involved in collisions were similar across both periods. Passenger cars were the most common vehicle type, with counts of 1,014 in December 2025 and 984 in December 2024. The top five vehicle makes involved in crashes were identical in both years: Toyota, Honda, Ford, Chevrolet, and Nissan, with only minor changes in their respective counts and rankings.
Top Vehicle Makes (1,527 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-12-01 to 2025-12-31 · 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: 2025-12-01 through 2025-12-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2025-12-01 through 2025-12-31 (31 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 875
- Total persons involved: 1,578
- Total vehicles involved: 1,527
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: December 2025." Published September 9, 2026. Reporting period: 2025-12-01 to 2025-12-31. 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/december-2025-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: 2025-12-01 – 2025-12-31
Generated: September 9, 2026 · All rights reserved