ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · AUGUST 2024
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-2024-report
Monthly Traffic Safety Analysis
851 CRASHES IN
MONTGOMERY, MD
AUGUST 2024
In August 2024, Montgomery County recorded 851 total crashes, a figure identical to the 851 crashes reported in August 2023. While the overall crash volume remained stable, the most notable year-over-year shift was a significant decrease in reported hit-and-run incidents, which fell from 215 to 18. Concurrently, the number of fatalities resulting from crashes increased from 1 to 4.
851
Total Crash Events
4
▲ 300.0%was 1
Persons Killed
298
▼ -12.1%was 339
Persons Injured
18
▼ -91.6%was 215
Hit-and-Run Crashes
Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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 · 2024-08-01 to 2024-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The total number of crashes in Montgomery County was unchanged year-over-year, with 851 incidents in both August 2024 and August 2023. However, the outcomes of these crashes shifted, with total injuries decreasing by 12.1% from 339 to 298. In contrast, fatalities increased from 1 in the prior period to 4 in the current period.
18
Hit-and-Run Crashes — August 2024
▼ -91.6% vs prior (215)
The number of hit-and-run crashes saw a substantial decrease year-over-year. In August 2024, there were 18 hit-and-run incidents, compared to 215 in August 2023, representing a 91.6% reduction in count. Consequently, the hit-and-run rate fell dramatically from 25.3% of all crashes in the prior year to 2.1% in the current period.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
26
Pedestrians Injured
7
Cyclists Injured
258
Motorists Injured
7
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-08-01 to 2024-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed a shift between August 2023 and August 2024. The peak day for crashes moved from Wednesday (154 crashes) in the prior year to Thursday (154 crashes) in the current year. The peak hour also shifted significantly from the midday hour of 12 p.m. (65 crashes) in August 2023 to the evening commute hour of 5 p.m. (69 crashes) in August 2024.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-08-01 to 2024-08-31 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-08-01 to 2024-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes remained constant, their severity profile changed year-over-year. The number of fatal crashes increased from 1 to 4, raising the fatal crash rate from 0.1% to 0.5% of all incidents. The share of serious injury crashes decreased from 2.5% to 1.5%, while the proportion of minor injury crashes grew from 12.8% to 16.7%.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-08-01 to 2024-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-08-01 to 2024-08-31 · Most severe injury per crash record
Top Contributing Factors
A direct year-over-year comparison of top contributing factors is not possible due to a change in how this data was categorized between the two periods. In August 2024, the leading factor was 'Failed to Yield Right-of-Way,' cited in 71 crashes, representing an 8.3% share of all crashes. In contrast, the data for August 2023 lists the top factor as 'RAIN, SNOW, WET,' associated with 31 crashes (3.6% share). The categories used in each period do not align for a direct comparison of driver behaviors.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-08-01 to 2024-08-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes on wet road surfaces increased from 69 in August 2023 to 100 in August 2024, a 44.9% rise in count. Similarly, the number of crashes occurring during rain grew from 50 to 89. Despite this, the share of crashes in clear weather also increased from 75.9% to 81.2%. Lighting conditions remained largely consistent, with approximately 75% of crashes in both periods happening during daylight.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-08-01 to 2024-08-31 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-08-01 to 2024-08-31 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-08-01 to 2024-08-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained Toyota, Honda, and Ford in both periods, though their counts shifted. The number of Toyotas involved increased from 193 to 271 and Hondas from 178 to 215, while Fords decreased from 149 to 137. Regarding vehicle types, the count of Passenger Cars involved in crashes decreased from 1,044 to 937, whereas Sport Utility Vehicles saw an increase from 148 to 243.
Top Vehicle Makes (1,475 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-08-01 to 2024-08-31 · 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: 2024-08-01 through 2024-08-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2024-08-01 through 2024-08-31 (31 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 851
- Total persons involved: 1,525
- Total vehicles involved: 1,475
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 2024." Published September 9, 2026. Reporting period: 2024-08-01 to 2024-08-31. 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-2024-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: 2024-08-01 – 2024-08-31
Generated: September 9, 2026 · All rights reserved