ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · NOVEMBER 2022
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/november-2022-report
Monthly Traffic Safety Analysis
927 CRASHES IN
MONTGOMERY, MD
NOVEMBER 2022
In November 2022, Montgomery County recorded 927 total crashes, a 2.9% increase from the 901 crashes reported in November 2021. While the total number of fatalities remained constant at four, the number of people injured rose by 10.1% from 278 to 306. A notable shift was the increase in crashes involving pedestrians, which grew from 39 to 48 year-over-year.
927
▲ 2.9%was 901
Total Crash Events
4
Persons Killed
306
▲ 10.1%was 278
Persons Injured
177
▼ -9.7%was 196
Hit-and-Run Crashes
Note: "Persons Killed" (4) 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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year, traffic crashes in Montgomery County showed a slight upward trend in November. Total crashes rose by 2.9%, from 901 in November 2021 to 927 in November 2022. Similarly, the number of people injured increased by 10.1% from 278 to 306, while total fatalities remained unchanged at four.
177
Hit-and-Run Crashes — November 2022
▼ -9.7% vs prior (196)
Hit-and-run incidents decreased in both absolute numbers and as a proportion of total crashes. In November 2022, there were 177 hit-and-run crashes, down from 196 in November 2021. This represents a drop in the hit-and-run rate from 21.8% of all crashes in the prior year to 19.1% in the current period.
Vulnerable Road User Casualties
3
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
44
Pedestrians Injured
4
Cyclists Injured
254
Motorists Injured
4
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-11-01 to 2022-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes in November remained largely consistent year-over-year. Tuesday was the peak day for crashes in both November 2022 (175 crashes) and November 2021 (165 crashes). The 5 p.m. hour was also the busiest hour in both periods, accounting for 83 crashes in 2022 and 75 in 2021, indicating no significant shift in daily or hourly crash patterns.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The rate of fatal crashes decreased from 0.55% (5 crashes) in November 2021 to 0.32% (3 crashes) in November 2022. However, the proportion of crashes resulting in any level of injury (serious, minor, or possible) increased from 25.9% of all incidents in the prior period to 27.4% in the current period. The count of crashes involving serious injuries also rose from 16 to 20.
Severity is per crash event (most severe injury). 3 fatal crash events resulted in 4 persons killed.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors cited in crash reports were consistent year-over-year, with weather and wet road conditions being most prominent. The count of crashes where 'RAIN, SNOW, WET' was a factor increased by 62.5%, from 32 in November 2021 to 52 in November 2022. Similarly, crashes with 'N/A, WET' as a factor rose by 50% from 32 to 48. In contrast, crashes involving animals decreased from 14 to 11.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Adverse weather and road conditions were more prevalent in crashes in November 2022 compared to the previous year. The number of crashes occurring in the rain increased from 65 to 101, and collisions on wet road surfaces rose from 87 to 140. Consequently, the share of all crashes occurring on wet roads grew from 9.7% to 15.1%. Lighting conditions at the time of crashes remained proportionally similar between the two periods.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-11-01 to 2022-11-30 · Road surface condition field
Vehicles & Demographics
The types and makes of vehicles involved in crashes remained stable year-over-year. Passenger cars were the most common vehicle type in both November 2022 (1098 vehicles) and November 2021 (1084 vehicles). The top three makes involved in collisions were Toyota, Honda, and Ford in both periods, with their relative rankings unchanged. Toyota-involved crashes increased from 213 to 235, and Honda-involved crashes rose from 172 to 193.
Top Vehicle Makes (1,608 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-11-01 to 2022-11-30 · 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: 2022-11-01 through 2022-11-30
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2022-11-01 through 2022-11-30 (30 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 927
- Total persons involved: 1,671
- Total vehicles involved: 1,608
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: November 2022." Published September 9, 2026. Reporting period: 2022-11-01 to 2022-11-30. 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/november-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
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Montgomery County Crash Reporting (ACRS) · Socrata
Period: 2022-11-01 – 2022-11-30
Generated: September 9, 2026 · All rights reserved