Monthly Traffic Safety Analysis

717 CRASHES IN
MONTGOMERY, MD
APRIL 2021

All metrics benchmarked againstApril 2020

In April 2021, Montgomery County recorded 717 total crashes, a 91.7% increase from the 374 crashes reported in April 2020. This year-over-year comparison shows a significant rise in overall crash volume. Alongside this increase, total fatalities rose from 1 to 5, and total injuries increased from 90 to 222.

717

91.7%was 374

Total Crash Events

5

400.0%was 1

Persons Killed

222

146.7%was 90

Persons Injured

146

75.9%was 83

Hit-and-Run Crashes

Note: "Persons Killed" (5) 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. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-04-01 to 2021-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for April indicates a sharply rising trend year-over-year. Total crashes increased by 91.7%, from 374 in April 2020 to 717 in April 2021. This was accompanied by a 146.7% increase in injuries (from 90 to 222) and a rise in fatalities from 1 to 5.

146

Hit-and-Run Crashes — April 2021

75.9% vs prior (83)

The total number of hit-and-run crashes increased by 75.9%, from 83 incidents in April 2020 to 146 in April 2021. Despite this rise in absolute numbers, the hit-and-run rate as a percentage of all crashes slightly decreased. The rate fell from 22.2% in the prior year to 20.4% in the current period.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

4

Motorists Killed

Prior: 1300.0%

0

Other Killed

Prior: 00.0%

25

Pedestrians Injured

Prior: 12108.3%

6

Cyclists Injured

Prior: 60.0%

189

Motorists Injured

Prior: 71166.2%

2

Other Injured

Prior: 1100.0%

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-04-01 to 2021-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted significantly between the two periods. In April 2021, the peak day for crashes was Friday with 139 incidents, and the peak hour was 5 PM with 65 incidents. This contrasts with April 2020, when the peak day was Thursday (71 crashes) and the peak hour was 12 PM (36 crashes), suggesting a shift in crash patterns from midday to the evening commute.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-04-01 to 2021-04-30 · Crash date field aggregated by weekday

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-04-01 to 2021-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The fatal crash rate increased from 0.27% in April 2020 to 0.7% in April 2021, with fatal crashes rising from 1 to 5. The overall proportion of crashes resulting in any level of injury (from possible to fatal) grew from a 20.6% share to a 27.8% share year-over-year. Correspondingly, the share of crashes with no reported injuries decreased from 78.3% in the prior period to 71.8% in the current period.

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.7%
400.0%prior 1
Serious Injury9serious injury crashes1.3%
28.6%prior 7
Minor Injury85minor injury crashes11.9%
183.3%prior 30
Possible Injury100possible injury crashes13.9%
156.4%prior 39
No Injury515no injury crashes71.8%
75.8%prior 293

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-04-01 to 2021-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-04-01 to 2021-04-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors were consistent year-over-year, though their counts changed. In April 2021, the top factor was 'RAIN, SNOW, WET' with 33 crashes, a decrease from 43 crashes in April 2020 where it was also the top factor. Conversely, crashes attributed to 'N/A, WET' increased from 16 to 23. Despite a 91.7% increase in total crashes, the count for the top identified contributing factor declined by 23.3%.

Officer-Reported Primary Contributing Cause

RAIN, SNOW, WET33 (4.6%)-23.3%prior 43
N/A, WET23 (3.2%)43.8%prior 16
N/A, RAIN, SNOW7 (1%)
N/A, V EXHAUST SYSTEM|R OTHER ROAD3 (0.4%)
N/A, VISION OBSTRUCTION (INCL. BLINDED BY SUN)3 (0.4%)
DEBRIS OR OBSTRUCTION, N/A3 (0.4%)
SLEET, HAIL, FREEZ. RAIN, WET2 (0.3%)
ICY OR SNOW-COVERED, N/A2 (0.3%)
ANIMAL, N/A2 (0.3%)-71.4%prior 7
RAIN, SNOW, ROAD UNDER CONSTRUCTION/MAINTENANCE1 (0.1%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-04-01 to 2021-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in April 2021 were more likely to occur in favorable conditions compared to the prior year. The proportion of crashes on dry roads increased from 61.0% to 73.2% of all crashes, while crashes on wet roads decreased from a 19.2% share to an 11.3% share. Similarly, crashes during clear weather constituted 68.7% of the total, up from 58.5% in April 2020, while the share of crashes in daylight decreased slightly from 69.0% to 65.5%.

Weather

Clear493 (76.0%)
125.1%prior 219
Cloudy92 (14.2%)
87.8%prior 49
Rain60 (9.2%)
-11.8%prior 68
Severe Crosswinds3 (0.5%)
Fog, Smog, Smoke1 (0.2%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-04-01 to 2021-04-30 · Weather condition at time of crash

Lighting

Daylight470 (67.0%)
82.2%prior 258
Dark - Lighted174 (24.8%)
132.0%prior 75
Dark - Not Lighted22 (3.1%)
83.3%prior 12
Dawn16 (2.3%)
77.8%prior 9
Dusk10 (1.4%)
-16.7%prior 12
Dark - Unknown Lighting8 (1.1%)
Other1 (0.1%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-04-01 to 2021-04-30 · Lighting condition field

Road Surface

Dry523 (86.0%)
129.4%prior 228
Wet81 (13.3%)
12.5%prior 72
Ice/Frost2 (0.3%)
Other1 (0.2%)
Water (standing, moving)1 (0.2%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-04-01 to 2021-04-30 · Road surface condition field

Vehicles & Demographics

Passenger cars remained the most common vehicle type involved in crashes, with their count more than doubling from 401 in April 2020 to 864 in April 2021. The top three vehicle makes involved in collisions were Toyota, Honda, and Ford in both periods. Toyota-involved crashes rose from 89 to 175, and Honda-involved crashes rose from 58 to 136. Data on driver age distribution was not available for comparison.

Top Vehicle Makes (1,226 vehicles)

1
TOYOTA175 (14.3%)
96.6%prior 89
2
HONDA136 (11.1%)
134.5%prior 58
3
FORD109 (8.9%)
39.7%prior 78
4
NISSAN63 (5.1%)
96.9%prior 32
5
DODGE48 (3.9%)
108.7%prior 23
6
HOND41 (3.3%)
241.7%prior 12
7
TOYT37 (3%)
68.2%prior 22
8
JEEP28 (2.3%)
366.7%prior 6
9
CHEVY26 (2.1%)
116.7%prior 12
10
KIA25 (2%)
92.3%prior 13

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-04-01 to 2021-04-30 · 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: 2021-04-01 through 2021-04-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2021-04-01 through 2021-04-30 (30 days)
  • Geographic scope: montgomery, MD
  • Total crash records analyzed: 717
  • Total persons involved: 1,261
  • Total vehicles involved: 1,226

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: April 2021." Published September 9, 2026. Reporting period: 2021-04-01 to 2021-04-30. 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/april-2021-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

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