ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · JANUARY 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/january-2026-report
Monthly Traffic Safety Analysis
782 CRASHES IN
MONTGOMERY, MD
JANUARY 2026
In January 2026, Montgomery County recorded 782 total crashes, a 7.8% decrease from the 848 crashes reported in January 2025. Despite the overall reduction in crashes, the most significant year-over-year change was the occurrence of 3 fatal crashes resulting in 2 fatalities, compared to zero in the prior year's period.
782
▼ -7.8%was 848
Total Crash Events
2
Persons Killed
218
▼ -7.6%was 236
Persons Injured
20
▼ -9.1%was 22
Hit-and-Run Crashes
Note: "Persons Killed" (2) 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. 43 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crashes in Montgomery County trended downward in January 2026 compared to the same month in the prior year. Total crashes fell by 7.8%, from 848 to 782. Similarly, the number of people injured in these incidents decreased by 7.6%, from 236 in January 2025 to 218 in January 2026.
20
Hit-and-Run Crashes — January 2026
▼ -9.1% vs prior (22)
The incidence of hit-and-run crashes remained stable year-over-year. In January 2026, there were 20 hit-and-run incidents, a slight decrease from 22 in January 2025. The hit-and-run rate, representing the percentage of total crashes that were hit-and-runs, was unchanged at 2.6% for both periods.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
32
Pedestrians Injured
7
Cyclists Injured
176
Motorists Injured
3
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-01-01 to 2026-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained largely consistent year-over-year. Friday was the peak day for crashes in both January 2026 (165 crashes) and January 2025 (158 crashes). The peak hour also held steady in the late afternoon, shifting slightly from the 3 PM hour in 2025 (69 crashes) to the 4 PM hour in 2026, which tied with the 3 PM hour for the most incidents (64 crashes each).
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-01-01 to 2026-01-31 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-01-01 to 2026-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes decreased, crash severity worsened in January 2026 with the recording of 3 fatal crashes (0.38% of total), compared to zero in January 2025. However, the number of crashes resulting in serious injuries saw a substantial decrease, falling from 20 (2.4% of total) in the prior year to 6 (0.8% of total) in the current period. The proportion of crashes resulting in either minor or possible injuries remained relatively stable year-over-year.
Severity is per crash event (most severe injury). 3 fatal crash events resulted in 2 persons killed.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-01-01 to 2026-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-01-01 to 2026-01-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor to crashes remained 'Failed to Yield Right-of-Way' in both periods, though its count decreased from 60 in January 2025 to 56 in January 2026. The second-ranked factor shifted, with 'Other Improper Action' increasing in count from 33 to 41, while crashes attributed to 'Followed Too Closely' decreased from 37 to 27. Crashes citing 'Too Fast For Conditions' also dropped from 19 incidents to 12.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-01-01 to 2026-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions were broadly similar year-over-year, with the majority of incidents in both periods occurring in daylight and on dry roads. However, there was a marked decrease in crashes happening during adverse weather, which fell from 131 incidents in January 2025 to 94 in January 2026. This corresponds with a drop in crashes on adverse road surfaces like snow, ice, and slush, which collectively accounted for 234 crashes in the prior period versus 169 in the current period.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-01-01 to 2026-01-31 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-01-01 to 2026-01-31 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-01-01 to 2026-01-31 · Road surface condition field
Vehicles & Demographics
The distribution of vehicle makes involved in crashes showed consistency between the two periods. Toyota, Honda, and Ford remained the top three most frequently involved makes in both January 2025 and January 2026, despite a decrease in the total number of vehicles for each. Similarly, Passenger Cars and Sport Utility Vehicles were the top two vehicle types involved in crashes for both years, with their counts decreasing from 938 to 837 and 241 to 207, respectively.
Top Vehicle Makes (1,343 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2026-01-01 to 2026-01-31 · 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: 2026-01-01 through 2026-01-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2026-01-01 through 2026-01-31 (31 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 782
- Total persons involved: 1,389
- Total vehicles involved: 1,343
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: January 2026." Published September 9, 2026. Reporting period: 2026-01-01 to 2026-01-31. 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/january-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: 2026-01-01 – 2026-01-31
Generated: September 9, 2026 · All rights reserved