ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · AUGUST 2025
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/august-2025-report
Monthly Traffic Safety Analysis
788 CRASHES IN
MONTGOMERY, MD
AUGUST 2025
In August 2025, Montgomery County recorded 788 total crashes, a 7.4% decrease from the 851 crashes reported in August 2024. While overall crashes and injuries declined, the number of crashes involving bicycles increased by 50% year-over-year, from 12 to 18 incidents. This was accompanied by a doubling of cyclist injuries, which rose from 7 to 14.
788
▼ -7.4%was 851
Total Crash Events
4
Persons Killed
289
▼ -3.0%was 298
Persons Injured
24
▲ 33.3%was 18
Hit-and-Run Crashes
Note: "Persons Killed" (4) 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. 39 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-08-01 to 2025-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Montgomery County saw a downward trend in August 2025 compared to the same month last year. The total number of crashes fell by 7.4%, from 851 to 788. Similarly, the number of people injured in these incidents decreased by 3.0% from 298 to 289, while total fatalities remained unchanged at four.
24
Hit-and-Run Crashes — August 2025
▲ 33.3% vs prior (18)
Hit-and-run incidents increased in August 2025 compared to the same month in 2024. The total count of hit-and-run crashes rose by 33.3%, from 18 to 24 incidents. Consequently, the hit-and-run rate, which measures these incidents as a percentage of all crashes, also trended upward, climbing from 2.1% in the prior year to 3.0% in the current period.
Vulnerable Road User Casualties
1
Pedestrians Killed
1
Cyclists Killed
2
Motorists Killed
0
Other Killed
23
Pedestrians Injured
14
Cyclists Injured
248
Motorists Injured
4
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-08-01 to 2025-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes showed some shifts between the two periods. While the evening commute hour of 5 p.m. remained the peak time for crashes in both August 2024 (69 crashes) and August 2025 (64 crashes), the most frequent day for incidents moved from Thursday (154 crashes) in the prior year to Friday (148 crashes) in the current year. Fridays and Saturdays were the days with the highest crash volumes in August 2025.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-08-01 to 2025-08-31 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-08-01 to 2025-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Although total crashes decreased, the severity of outcomes increased in August 2025 compared to the prior year. The fatal crash rate rose from 0.47 to 0.63 per 100 crashes, and the number of fatal crashes increased from 4 to 5. The count of serious injury crashes also grew significantly, rising from 13 to 21. Crashes resulting in possible or minor injuries saw a decrease in count.
Severity is per crash event (most severe injury). 5 fatal crash events resulted in 4 persons killed.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-08-01 to 2025-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-08-01 to 2025-08-31 · Most severe injury per crash record
Top Contributing Factors
The top three contributing factors remained consistent across both periods, led by 'Failed to Yield Right-of-Way' in both August 2024 (71 crashes) and August 2025 (62 crashes). While the counts for the top three factors declined, crashes attributed to 'Improper Backing' more than doubled, with the count increasing from 8 to 18. Additionally, crashes involving an 'Inattentive, Careless, Negligent, or Erratic Manner' of operation increased in count from 15 to 20.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-08-01 to 2025-08-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in August 2025 occurred under more favorable weather and road conditions compared to August 2024. The number of crashes during rainfall decreased from 89 to 36, and incidents on wet roads fell from 100 to 46. The proportion of crashes occurring in daylight remained stable at approximately 75% for both periods, while crashes on dark, unlit roads decreased from 38 to 21.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-08-01 to 2025-08-31 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-08-01 to 2025-08-31 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-08-01 to 2025-08-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes remained largely similar, with Toyota and Honda leading in both periods. However, the number of Hondas involved decreased from 215 to 181 year-over-year. A notable change was the increase in Teslas involved in crashes, which more than doubled from 11 in August 2024 to 27 in August 2025. Chevrolet entered the top five most-involved makes, replacing Hyundai from the prior year's list.
Top Vehicle Makes (1,368 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2025-08-01 to 2025-08-31 · 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: 2025-08-01 through 2025-08-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2025-08-01 through 2025-08-31 (31 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 788
- Total persons involved: 1,421
- Total vehicles involved: 1,368
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: August 2025." Published September 9, 2026. Reporting period: 2025-08-01 to 2025-08-31. 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/august-2025-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: 2025-08-01 – 2025-08-31
Generated: September 9, 2026 · All rights reserved