ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · 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/2024-annual-report
Yearly Traffic Safety Analysis
10,629 CRASHES IN
MONTGOMERY, MD
2024
In 2024, Montgomery County recorded 10,629 total traffic crashes, a 1.4% decrease from the 10,776 crashes reported in 2023. While overall crashes declined slightly, the number of fatalities rose from 31 to 34. The most significant year-over-year change was a fundamental shift in how contributing factors were categorized, preventing a direct comparison of driver behaviors between the two periods.
10,629
▼ -1.4%was 10,776
Total Crash Events
34
▲ 9.7%was 31
Persons Killed
3,628
▼ -0.4%was 3,644
Persons Injured
265
▼ -88.3%was 2,261
Hit-and-Run Crashes
Note: "Persons Killed" (34) counts individual fatalities across all crash events. "Fatal" in the severity table below (36) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 458 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crashes in Montgomery County saw a slight downward trend, decreasing by 1.4% from 10,776 in 2023 to 10,629 in 2024. Despite the drop in total incidents, the number of people killed in crashes increased from 31 to 34 year-over-year. The total number of injuries remained stable, with 3,628 in 2024 compared to 3,644 in 2023.
265
Hit-and-Run Crashes — 2024
▼ -88.3% vs prior (2,261)
The number of reported hit-and-run incidents saw a substantial decrease from 2,261 in 2023 to 265 in 2024. Consequently, the hit-and-run rate fell sharply from 21.0% of all crashes in the prior year to 2.5% in the current year. This represents a significant downward trend in reported hit-and-run events.
Vulnerable Road User Casualties
16
Pedestrians Killed
0
Cyclists Killed
18
Motorists Killed
0
Other Killed
451
Pedestrians Injured
109
Cyclists Injured
3,009
Motorists Injured
59
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-01-01 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 remained highly consistent between the two years. Friday was the peak day for crashes in both 2024 (1,688 crashes) and 2023 (1,689 crashes). Similarly, the 3 PM hour was the peak time for incidents in both 2024, with 840 crashes, and 2023, with 815 crashes.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate saw a minor increase from 0.32 in 2023 to 0.34 in 2024, with total fatalities rising from 31 to 34. The distribution of injury severity shifted, as crashes resulting in minor injuries increased their share from 11.4% to 16.4% of all incidents. Conversely, the proportion of crashes with possible injuries decreased from 15.3% to 10.6%.
Severity is per crash event (most severe injury). 36 fatal crash events resulted in 34 persons killed.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
A direct year-over-year comparison of contributing factors is not feasible due to a significant change in data classification between periods. The 2023 data primarily categorized factors by environmental or road conditions, with 'RAIN, SNOW, WET' being the top factor (681 crashes). In contrast, the 2024 data focused on driver actions, with 'Failed to Yield Right-of-Way' listed as the top factor, contributing to 953 crashes, or 9% of the total.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes across environmental conditions was largely stable year-over-year. In 2024, 77.4% of crashes occurred in 'Clear' weather, compared to 70.8% in 2023. Crashes on 'Dry' road surfaces accounted for 71.1% of incidents in 2024 and 69.4% in 2023, while crashes in 'Daylight' represented 66.7% and 64.5% of the total in each respective year.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
Passenger cars and Sport Utility Vehicles were the most frequently involved vehicle types in both periods. The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained the same across both years. After normalizing for data entry variations in the 2023 data, the number of vehicles from these top makes involved in crashes remained relatively stable year-over-year.
Top Vehicle Makes (18,600 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2024-01-01 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: 2024-01-01 through 2024-12-31
- Report generated: August 4, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 10,629
- Total persons involved: 19,315
- Total vehicles involved: 18,600
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: 2024." Published August 4, 2026. Reporting period: 2024-01-01 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/2024-annual-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: 2024-01-01 – 2024-12-31
Generated: August 4, 2026 · All rights reserved