ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · JULY 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/july-2024-report
Monthly Traffic Safety Analysis
853 CRASHES IN
MONTGOMERY, MD
JULY 2024
In July 2024, Montgomery County recorded 853 total crashes, a 3.1% increase from the 827 crashes documented in July 2023. While overall crashes and injuries saw a slight rise, the most significant year-over-year change was a substantial decrease in reported hit-and-run incidents, which fell from 187 to 30.
853
▲ 3.1%was 827
Total Crash Events
5
▼ -16.7%was 6
Persons Killed
298
▲ 4.9%was 284
Persons Injured
30
▼ -84.0%was 187
Hit-and-Run Crashes
Note: "Persons Killed" (5) 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. 46 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-07-01 to 2024-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic collisions in Montgomery County saw a slight increase in July 2024 compared to the same month in the prior year. The total number of crashes rose by 3.1%, from 827 to 853. The number of persons injured also increased by 4.9% from 284 to 298, while the number of fatalities decreased from 6 to 5.
30
Hit-and-Run Crashes — July 2024
▼ -84.0% vs prior (187)
There was a significant year-over-year decrease in hit-and-run crashes. The number of such incidents dropped by 84.0%, from 187 in July 2023 to 30 in July 2024. Consequently, the hit-and-run rate as a percentage of all crashes fell dramatically from 22.6% to 3.5%.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
4
Motorists Killed
0
Other Killed
30
Pedestrians Injured
15
Cyclists Injured
247
Motorists Injured
6
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-07-01 to 2024-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained broadly consistent year-over-year. Monday was the peak day for crashes in both July 2024 (144 crashes) and July 2023 (136 crashes). The peak hour for collisions shifted slightly later in the day, moving from the 3 PM hour in the prior year (76 crashes) to the 4 PM hour in the current period (69 crashes).
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-07-01 to 2024-07-31 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-07-01 to 2024-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the total number of fatal crashes decreased from 6 to 5 year-over-year, the distribution of injury severity shifted. The proportion of crashes resulting in serious injuries increased from 1.6% to 2.2% of all collisions, and minor injury crashes grew from a 12.3% share to a 16.8% share. Conversely, crashes categorized with possible injury or no injury both saw a decrease in their proportion of the total.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-07-01 to 2024-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-07-01 to 2024-07-31 · Most severe injury per crash record
Top Contributing Factors
A direct year-over-year comparison of contributing factors is not possible due to a change in how this data was categorized between the two periods. In July 2024, the leading documented driver action contributing to crashes was 'Failed to Yield Right-of-Way,' cited in 70 incidents (an 8.2% share of all crashes). In contrast, the data for July 2023 categorized factors differently, with the top entry being a combination of road and weather conditions rather than specific driver behaviors.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-07-01 to 2024-07-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of environmental conditions during crashes remained largely stable between July 2023 and July 2024. Daylight conditions accounted for 75.0% of crashes in both periods, and crashes on dry road surfaces also held a consistent share at approximately 76-77% across both years. The number of crashes occurring during rain increased from 49 to 59, though this did not represent a significant change in the overall proportion.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-07-01 to 2024-07-31 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-07-01 to 2024-07-31 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-07-01 to 2024-07-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in collisions remained consistent, with Toyota, Honda, and Ford leading in both July 2023 and July 2024. In the current period, Toyota was the most common make with 269 vehicles involved, followed by Honda with 223. When looking at vehicle types, the number of Passenger Cars involved in crashes decreased from 1,031 to 912, while the number of Sport Utility Vehicles involved increased from 160 to 255.
Top Vehicle Makes (1,471 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-07-01 to 2024-07-31 · 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: 2024-07-01 through 2024-07-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2024-07-01 through 2024-07-31 (31 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 853
- Total persons involved: 1,529
- Total vehicles involved: 1,471
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: July 2024." Published September 9, 2026. Reporting period: 2024-07-01 to 2024-07-31. 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/july-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: 2024-07-01 – 2024-07-31
Generated: September 9, 2026 · All rights reserved