ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · NOVEMBER 2023
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-2023-report
Monthly Traffic Safety Analysis
1,008 CRASHES IN
MONTGOMERY, MD
NOVEMBER 2023
In November 2023, Montgomery County recorded 1,008 total crashes, an 8.7% increase from the 927 crashes reported in November 2022. Despite the rise in total collisions, the number of fatalities decreased from four in the prior period to one in the current period. Overall injuries also saw an increase from 306 to 335 year-over-year.
1,008
▲ 8.7%was 927
Total Crash Events
1
▼ -75.0%was 4
Persons Killed
335
▲ 9.5%was 306
Persons Injured
206
▲ 16.4%was 177
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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year data for November indicates an upward trend in total traffic collisions in Montgomery County. Crashes increased by 8.7%, from 927 in November 2022 to 1,008 in November 2023. Similarly, the number of people injured rose by 9.5% from 306 to 335, while fatalities saw a notable decrease from four to one.
206
Hit-and-Run Crashes — November 2023
▲ 16.4% vs prior (177)
Hit-and-run incidents increased in both absolute numbers and as a percentage of total crashes year-over-year. The count of hit-and-run crashes rose from 177 in November 2022 to 206 in November 2023, a 16.4% increase. This pushed the hit-and-run rate up from 19.1% to 20.4% of all crashes during the period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
50
Pedestrians Injured
6
Cyclists Injured
277
Motorists Injured
2
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-11-01 to 2023-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts between November 2022 and November 2023. While the peak hour for collisions remained constant at 5 p.m. with 83 crashes in both periods, the peak day changed. Wednesday became the most frequent day for crashes with 196 incidents in November 2023, a shift from Tuesday, which was the peak day in the prior year with 175 crashes.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity saw a mixed but generally less severe profile in November 2023 compared to the previous year. The number of fatal crashes decreased from 3 to 1, lowering the fatal crash rate from 0.3% to 0.1% of all incidents. While the proportion of serious injury crashes remained stable at approximately 2.1%, crashes involving possible injuries increased from 14.6% to 16.3% of all incidents.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes remained consistent year-over-year, with weather-related issues prominent. The top factor in both periods was 'RAIN, SNOW, WET', with its count increasing from 52 to 56 crashes. The second-ranked factor, 'N/A, WET', saw a slight decrease in count from 48 to 44 incidents. Crashes involving animals ('ANIMAL, N/A') increased in count from 11 to 16, but this factor remained the third most common in both November 2022 and 2023.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
In November 2023, a larger proportion of crashes occurred in clear weather and on dry roads compared to the same month in 2022. Crashes in clear conditions rose from 71.2% to 76.0% of the total, while incidents on dry road surfaces increased from 71.1% to 74.4%. Correspondingly, the share of crashes occurring in rain decreased from 10.9% to 9.7%. The distribution of crashes by lighting condition remained relatively stable, with crashes in daylight accounting for 52.3% of the total, down slightly from 53.2% the prior year.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-11-01 to 2023-11-30 · Road surface condition field
Vehicles & Demographics
Passenger cars remained the most common vehicle type involved in crashes, with 1,224 involved in November 2023 compared to 1,098 in November 2022. The top three vehicle makes involved in collisions were Toyota, Honda, and Ford in both periods, though their order shifted. While Toyota remained the most frequent make, Ford's involvement increased from 161 to 173 vehicles, moving it to the second-ranked position ahead of Honda, which saw its involvement decrease from 193 to 172 vehicles.
Top Vehicle Makes (1,765 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2023-11-01 through 2023-11-30 (30 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 1,008
- Total persons involved: 1,834
- Total vehicles involved: 1,765
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 2023." Published September 9, 2026. Reporting period: 2023-11-01 to 2023-11-30. 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-2023-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: 2023-11-01 – 2023-11-30
Generated: September 9, 2026 · All rights reserved