ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · DECEMBER 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/december-2024-report
Monthly Traffic Safety Analysis
871 CRASHES IN
MONTGOMERY, MD
DECEMBER 2024
In December 2024, Montgomery County recorded 871 total crashes, a 7.7% decrease from the 944 crashes documented in December 2023. While overall crashes declined, the most notable year-over-year shift was a substantial decrease in reported hit-and-run incidents, which fell from 170 to 23. Fatalities also decreased from two to one.
871
▼ -7.7%was 944
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
304
▼ -4.4%was 318
Persons Injured
23
▼ -86.5%was 170
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. 29 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, traffic crashes in Montgomery County saw a downward trend in December 2024 compared to the same month in the previous year. Total crashes decreased by 7.7%, from 944 to 871. Correspondingly, the number of people injured fell by 4.4% from 318 to 304, and fatalities decreased from two to one.
23
Hit-and-Run Crashes — December 2024
▼ -86.5% vs prior (170)
There was a significant year-over-year decrease in hit-and-run incidents. In December 2024, there were 23 hit-and-run crashes, representing a rate of 2.6% of all collisions. This marks a substantial drop from December 2023, which recorded 170 hit-and-run crashes at a rate of 18.0%.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
56
Pedestrians Injured
5
Cyclists Injured
238
Motorists Injured
5
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-12-01 to 2024-12-31 · 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 the two periods. In December 2024, the peak day for crashes was Tuesday with 144 incidents, and the peak hour was 6 PM with 70 incidents. This contrasts with December 2023, when Friday was the busiest day with 179 crashes and the 5 PM hour was the peak time with 79 crashes.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes showed a mixed profile year-over-year, even as the fatal crash rate decreased from 0.21% to 0.11%. The share of crashes resulting in serious injuries increased from 1.7% to 2.4%, and minor injury crashes rose from 10.0% to 16.2% of all incidents. Consequently, the proportion of crashes with no reported injuries decreased from 71.0% in the prior period to 65.8% in the current period.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The methodology for recording contributing factors changed significantly between the two periods, preventing a direct year-over-year comparison of specific causes. In December 2024, the data focused on driver actions, with 'Failed to Yield Right-of-Way' being the top factor, cited in 59 crashes. In contrast, the data for December 2023 primarily captured environmental conditions, with 'RAIN, SNOW, WET' being the most common factor, listed for 107 incidents.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in both periods predominantly occurred in clear weather and daylight. However, the proportion of crashes under these favorable conditions was higher in December 2024, with clear-weather crashes making up 69.8% of the total compared to 60.8% the prior year. Similarly, incidents during daylight hours rose from 47.5% to 54.1% of all crashes, while the share of crashes on dry road surfaces remained stable at approximately 60% for both periods.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes remained consistent, with Toyota, Honda, and Ford leading in both periods. In December 2024, these makes were involved in 286, 230, and 131 crashes, respectively. While direct count comparisons are affected by data entry variations in the prior year's records, the ranking of the top makes did not change. Passenger Cars and Sport Utility Vehicles were the most common vehicle types involved in collisions in both December 2023 and December 2024.
Top Vehicle Makes (1,532 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-12-01 to 2024-12-31 · 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: 2024-12-01 through 2024-12-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2024-12-01 through 2024-12-31 (31 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 871
- Total persons involved: 1,603
- Total vehicles involved: 1,532
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: December 2024." Published September 9, 2026. Reporting period: 2024-12-01 to 2024-12-31. 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/december-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: 2024-12-01 – 2024-12-31
Generated: September 9, 2026 · All rights reserved