ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · SEPTEMBER 2021
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/september-2021-report
Monthly Traffic Safety Analysis
917 CRASHES IN
MONTGOMERY, MD
SEPTEMBER 2021
In September 2021, Montgomery County recorded 917 total traffic crashes, a 34.5% increase from the 682 crashes documented in September 2020. This year-over-year rise was accompanied by a significant increase in crash severity, with total fatalities more than doubling from 3 to 7. The total number of people injured also rose from 253 to 345.
917
▲ 34.5%was 682
Total Crash Events
7
▲ 133.3%was 3
Persons Killed
345
▲ 36.4%was 253
Persons Injured
179
▲ 23.4%was 145
Hit-and-Run Crashes
Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (7) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-09-01 to 2021-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data for Montgomery County indicates a rising trend in collisions when comparing September 2021 to the same month in the prior year. Total crashes increased by 34.5%, from 682 to 917. Similarly, the human cost of these incidents grew, with total fatalities rising from 3 to 7 and the number of injuries increasing by 36.4% from 253 to 345.
179
Hit-and-Run Crashes — September 2021
▲ 23.4% vs prior (145)
The absolute number of hit-and-run incidents increased from 145 in September 2020 to 179 in September 2021, a 23.4% rise. However, because the total number of crashes grew at a faster pace, the hit-and-run rate as a percentage of all crashes trended downward. The rate decreased from 21.3% in the prior year to 19.5% in the current period.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
6
Motorists Killed
0
Other Killed
29
Pedestrians Injured
12
Cyclists Injured
299
Motorists Injured
5
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-09-01 to 2021-09-30 · 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 consistent year-over-year, though the volume of incidents increased. Wednesday was the peak day for crashes in both September 2021 (197 crashes) and September 2020 (133 crashes). The peak hour also held steady in the afternoon commute, with the 4 p.m. hour seeing the most crashes in both periods, increasing from 53 incidents in 2020 to 74 in 2021.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-09-01 to 2021-09-30 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-09-01 to 2021-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity worsened in September 2021 compared to the previous year. The number of fatal crashes increased from 3 to 7, and the fatal crash rate nearly doubled from 0.4% to 0.8% of all crashes. While the absolute number of crashes involving any injury rose from 215 to 276, their proportion of total crashes saw a slight decrease from 31.5% in 2020 to 30.1% in 2021.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-09-01 to 2021-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-09-01 to 2021-09-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent between the two periods, though their absolute counts increased. The top-ranked factor in both years was "RAIN, SNOW, WET," with the count of related crashes rising from 59 to 71, a 20.3% increase in count. However, its share of all contributing factors decreased from 8.7% to 7.7%. Similarly, the second-ranked factor, "N/A, WET," saw its count increase from 33 to 35, while its share of the total fell from 4.8% to 3.8%.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-09-01 to 2021-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Comparing September 2021 to September 2020, a larger proportion of crashes occurred in clear weather and on dry roads. Crashes in 'Clear' weather conditions increased from 63.2% to 75.1% of the total, while crashes on 'Dry' road surfaces rose from 67.6% to 69.7% of the total. The distribution of crashes by lighting conditions remained stable, with 'Daylight' crashes accounting for 69.4% of incidents in 2021, compared to 66.6% in 2020.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-09-01 to 2021-09-30 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-09-01 to 2021-09-30 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-09-01 to 2021-09-30 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes were the same in both periods, with their numbers increasing in line with the overall trend. Toyota, Honda, and Ford were the most frequent makes in both September 2020 and September 2021. The involvement of Toyotas increased from 188 to 246 vehicles, Hondas from 154 to 184, and Fords from 110 to 146. The overall distribution of vehicle types, led by Passenger Cars and (Sport) Utility Vehicles, also remained consistent year-over-year.
Top Vehicle Makes (1,618 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-09-01 to 2021-09-30 · 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: 2021-09-01 through 2021-09-30
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2021-09-01 through 2021-09-30 (30 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 917
- Total persons involved: 1,674
- Total vehicles involved: 1,618
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: September 2021." Published September 9, 2026. Reporting period: 2021-09-01 to 2021-09-30. 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/september-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Montgomery County Crash Reporting (ACRS) · Socrata
Period: 2021-09-01 – 2021-09-30
Generated: September 9, 2026 · All rights reserved