ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · OCTOBER 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/october-2022-report
Monthly Traffic Safety Analysis
979 CRASHES IN
MONTGOMERY, MD
OCTOBER 2022
In October 2022, Montgomery County recorded 979 traffic crashes, a slight decrease from the 981 crashes reported in October 2021. While the overall crash volume remained stable with a 0.2% decrease, the number of fatalities saw a significant increase, rising from zero in the prior year period to seven in the current period. This increase in fatalities occurred despite a small drop in the total number of injuries.
979
▼ -0.2%was 981
Total Crash Events
7
Persons Killed
336
▼ -4.0%was 350
Persons Injured
201
▲ 3.1%was 195
Hit-and-Run Crashes
Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) 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 · 2022-10-01 to 2022-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year, the total number of crashes in Montgomery County remained nearly stable, decreasing by just 0.2% from 981 in October 2021 to 979 in October 2022. The total number of injuries also saw a modest decline of 4.0%, from 350 to 336. However, this period was marked by a significant rise in fatalities from zero to seven.
201
Hit-and-Run Crashes — October 2022
▲ 3.1% vs prior (195)
The number of hit-and-run incidents saw a slight increase, rising from 195 in October 2021 to 201 in October 2022. This represents a 3.1% increase in the count of hit-and-run crashes. The hit-and-run rate, which measures the proportion of all crashes that are hit-and-runs, also trended slightly upward from 19.9% to 20.5%.
Vulnerable Road User Casualties
2
Pedestrians Killed
1
Cyclists Killed
4
Motorists Killed
0
Other Killed
40
Pedestrians Injured
6
Cyclists Injured
287
Motorists Injured
3
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-10-01 to 2022-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between October 2021 and October 2022. The peak day for crashes moved from Friday (200 crashes) in the prior year to Monday (170 crashes) in the current period. Similarly, the peak hour for collisions changed from the afternoon commute at 4 p.m. (78 crashes) in 2021 to the morning commute at 8 a.m. (74 crashes) in 2022.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-10-01 to 2022-10-31 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-10-01 to 2022-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased notably in October 2022 compared to the same month in 2021, primarily driven by a rise in fatalities from zero to seven. Consequently, the fatal crash rate increased from 0.1% to 0.82%. While the count of serious injury crashes remained unchanged at 19, the number of minor injury crashes grew from 107 to 134. Conversely, crashes resulting in possible injuries decreased from 164 to 132.
Severity is per crash event (most severe injury). 8 fatal crash events resulted in 7 persons killed.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-10-01 to 2022-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-10-01 to 2022-10-31 · Most severe injury per crash record
Top Contributing Factors
In both periods, wet conditions were the most cited contributing factor. The top factor, 'RAIN, SNOW, WET,' was associated with 107 crashes in October 2022, a 123% increase from the 48 crashes recorded in October 2021. Similarly, crashes linked to the factor 'N/A, WET' increased by 90%, from 31 to 59. The number of crashes involving animals as a factor decreased from 9 in the prior period to 5 in the current period.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-10-01 to 2022-10-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring in adverse weather and road conditions increased significantly year-over-year. Crashes in the rain rose from 90 in October 2021 to 172 in October 2022, while collisions on wet road surfaces more than doubled from 107 to 225. Correspondingly, crashes on dry roads and in clear weather saw a decrease. Lighting conditions remained relatively stable, with a similar number of crashes occurring in daylight in both periods (598 in 2022 vs. 583 in 2021).
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-10-01 to 2022-10-31 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-10-01 to 2022-10-31 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-10-01 to 2022-10-31 · Road surface condition field
Vehicles & Demographics
The distribution of vehicle makes involved in crashes remained consistent year-over-year. In both October 2022 and October 2021, the top three makes were Toyota, Honda, and Ford, with nearly identical involvement counts. A notable shift occurred in vehicle types, with (Sport) Utility Vehicles involved in 190 crashes in the current period, up from 145 in the prior year. Conversely, passenger car involvement decreased from 1227 to 1156.
Top Vehicle Makes (1,731 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-10-01 to 2022-10-31 · 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: 2022-10-01 through 2022-10-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2022-10-01 through 2022-10-31 (31 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 979
- Total persons involved: 1,791
- Total vehicles involved: 1,731
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: October 2022." Published September 9, 2026. Reporting period: 2022-10-01 to 2022-10-31. 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/october-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: 2022-10-01 – 2022-10-31
Generated: September 9, 2026 · All rights reserved