Monthly Traffic Safety Analysis

714 CRASHES IN
MONTGOMERY, MD
FEBRUARY 2022

All metrics benchmarked againstFebruary 2021

In February 2022, Montgomery County recorded 714 total vehicle crashes, a 40% increase from the 510 crashes documented in February 2021. This rise in collisions was accompanied by an increase in total injuries from 137 to 224. Notably, the county registered one traffic fatality in February 2022, whereas none were recorded in the same month of the prior year.

714

40.0%was 510

Total Crash Events

1

Persons Killed

224

63.5%was 137

Persons Injured

167

62.1%was 103

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-02-01 to 2022-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for Montgomery County indicates a rising trend year-over-year. Total crashes increased by 40% from 510 in February 2021 to 714 in February 2022. Similarly, the number of people injured in these incidents grew by 63.5%, from 137 to 224, and one fatality was recorded compared to zero in the previous period.

167

Hit-and-Run Crashes — February 2022

62.1% vs prior (103)

Hit-and-run incidents increased in both count and as a proportion of total crashes. The number of hit-and-run crashes rose from 103 in February 2021 to 167 in February 2022, representing a 62% increase. Consequently, the hit-and-run rate climbed from 20.2% of all crashes in the prior period to 23.4% in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

34

Pedestrians Injured

Prior: 7385.7%

6

Cyclists Injured

Prior: 520.0%

182

Motorists Injured

Prior: 12446.8%

2

Other Injured

Prior: 1100.0%

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-02-01 to 2022-02-28 · 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 some shifts between the two periods. The peak day for collisions moved from Wednesday (98 crashes) in February 2021 to Tuesday (120 crashes) in February 2022. While the afternoon commute remained the most frequent time for incidents, the volume at the 3 PM peak hour increased by 60%, from 40 crashes in 2021 to 64 in 2022.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-02-01 to 2022-02-28 · Crash date field aggregated by weekday

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-02-01 to 2022-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the overall proportion of crashes resulting in an injury remained stable at approximately 25%, the absolute numbers reflect a more severe outcome year-over-year. A fatal crash occurred in February 2022, resulting in one death, compared to zero fatalities in February 2021. The count of serious injury crashes increased from 9 to 15, and the number of persons receiving serious injuries doubled from 9 to 18.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.1%
Serious Injury15serious injury crashes2.1%
66.7%prior 9
Minor Injury64minor injury crashes9%
23.1%prior 52
Possible Injury100possible injury crashes14%
56.3%prior 64
No Injury531no injury crashes74.4%
40.1%prior 379

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-02-01 to 2022-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-02-01 to 2022-02-28 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors shifted, likely reflecting different weather patterns between the two months. In February 2021, the top factor was 'ICY OR SNOW-COVERED, SLEET, HAIL, FREEZ. RAIN' with 32 crashes. In February 2022, this factor accounted for only two crashes, while 'RAIN, SNOW, WET' became the leading cause with 45 crashes, a 61% increase in count from the 28 crashes attributed to it in the prior year.

Officer-Reported Primary Contributing Cause

RAIN, SNOW, WET45 (6.3%)60.7%prior 28
N/A, WET31 (4.3%)3.3%prior 30
ANIMAL, N/A7 (1%)
N/A, VISION OBSTRUCTION (INCL. BLINDED BY SUN)6 (0.8%)
N/A, RAIN, SNOW6 (0.8%)
SLEET, HAIL, FREEZ. RAIN, WET4 (0.6%)-55.6%prior 9
BACKUP DUE TO REGULAR CONGESTION, N/A3 (0.4%)
ICY OR SNOW-COVERED, SLEET, HAIL, FREEZ. RAIN2 (0.3%)-93.8%prior 32
ICY OR SNOW-COVERED, RAIN, SNOW, WET2 (0.3%)
DEBRIS OR OBSTRUCTION, N/A2 (0.3%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-02-01 to 2022-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A significant difference in environmental conditions was observed between the two periods. In February 2022, over 70% of crashes occurred on dry roads under clear skies, compared to just 48% on dry roads and 52% in clear weather in February 2021. The prior year's data shows a much higher incidence of crashes on roads affected by ice, slush, or snow, which were minimal factors in the current period. Lighting conditions, however, remained consistent, with about 56.5% of crashes in both periods occurring in daylight.

Weather

Clear503 (77.7%)
88.4%prior 267
Rain81 (12.5%)
84.1%prior 44
Cloudy43 (6.6%)
-30.6%prior 62
Fog, Smog, Smoke6 (0.9%)
Severe Crosswinds5 (0.8%)
Snow5 (0.8%)
-87.2%prior 39
Wintry Mix2 (0.3%)
-93.1%prior 29
Sleet Or Hail1 (0.2%)
-95.0%prior 20
Other1 (0.2%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-02-01 to 2022-02-28 · Weather condition at time of crash

Lighting

Daylight404 (57.5%)
40.3%prior 288
Dark - Lighted240 (34.2%)
48.1%prior 162
Dark - Not Lighted25 (3.6%)
-10.7%prior 28
Dusk13 (1.9%)
30.0%prior 10
Dawn13 (1.9%)
85.7%prior 7
Dark - Unknown Lighting4 (0.6%)
Other3 (0.4%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-02-01 to 2022-02-28 · Lighting condition field

Road Surface

Dry504 (82.1%)
104.9%prior 246
Wet106 (17.3%)
-4.5%prior 111
Ice/Frost4 (0.7%)
-88.2%prior 34

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-02-01 to 2022-02-28 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in collisions—Toyota, Honda, and Ford—were consistent across both years, with each showing an increased count in February 2022. Passenger cars remained the predominant vehicle type, with their involvement growing from 569 in 2021 to 859 in 2022. The number of SUVs in crashes also rose from 79 to 120.

Top Vehicle Makes (1,228 vehicles)

1
TOYOTA159 (12.9%)
38.3%prior 115
2
HONDA154 (12.5%)
42.6%prior 108
3
FORD118 (9.6%)
12.4%prior 105
4
NISSAN59 (4.8%)
25.5%prior 47
5
TOYT55 (4.5%)
71.9%prior 32
6
CHEVROLET33 (2.7%)
50.0%prior 22
7
CHEVY30 (2.4%)
87.5%prior 16
8
HOND29 (2.4%)
11.5%prior 26
9
BMW29 (2.4%)
107.1%prior 14
10
HYUNDAI28 (2.3%)
100.0%prior 14

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-02-01 to 2022-02-28 · 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: 2022-02-01 through 2022-02-28
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2022-02-01 through 2022-02-28 (28 days)
  • Geographic scope: montgomery, MD
  • Total crash records analyzed: 714
  • Total persons involved: 1,272
  • Total vehicles involved: 1,228

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: February 2022." Published September 9, 2026. Reporting period: 2022-02-01 to 2022-02-28. 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/february-2022-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