ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · DECEMBER 2023
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-2023-report
Monthly Traffic Safety Analysis
944 CRASHES IN
MONTGOMERY, MD
DECEMBER 2023
In December 2023, Montgomery County recorded 944 total crashes, a 2.5% decrease from the 968 crashes reported in December 2022. While overall collisions and fatalities declined, the total number of people injured increased by 9.3% from 291 to 318. The most notable year-over-year shift was a 100% increase in crashes resulting in serious injuries, which doubled from 8 to 16.
944
▼ -2.5%was 968
Total Crash Events
2
▼ -33.3%was 3
Persons Killed
318
▲ 9.3%was 291
Persons Injured
170
▼ -8.6%was 186
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-12-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year, total crashes in Montgomery County saw a slight decline in December, falling by 2.5% from 968 in 2022 to 944 in 2023. Despite this decrease in overall collisions, the number of people injured increased by 9.3%, rising from 291 to 318. The number of persons killed in crashes decreased from 3 to 2.
170
Hit-and-Run Crashes — December 2023
▼ -8.6% vs prior (186)
Hit-and-run incidents decreased in both absolute numbers and as a percentage of total crashes. In December 2023, there were 170 hit-and-run crashes, down from 186 in December 2022. This represents a drop in the hit-and-run rate from 19.2% to 18.0% of all crashes year-over-year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
29
Pedestrians Injured
6
Cyclists Injured
282
Motorists Injured
1
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-12-01 to 2023-12-31 · 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 consistent year-over-year, with Friday being the peak day for crashes in both December 2023 (179 crashes) and December 2022 (201 crashes). Similarly, the 5 PM hour was the single hour with the most crashes in both periods. This peak hour accounted for 79 crashes in 2023 and 85 in 2022.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-12-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-12-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the number of fatal crashes decreased from 3 to 2 year-over-year, the overall severity of crashes increased. The count of crashes resulting in serious injuries doubled from 8 in December 2022 to 16 in December 2023, raising their share of all crashes from 0.8% to 1.7%. Consequently, the proportion of crashes resulting in no injuries fell from 75.3% to 71.0%.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-12-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-12-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors cited in crash reports were consistent across both periods, with weather-related conditions being dominant. In December 2023, "RAIN, SNOW, WET" was the top factor, cited in 107 crashes, which is an increase from 93 crashes in December 2022 and represents a 15% increase in count. The second most common factor, "N/A, WET," also held its rank, with its count remaining stable at 62 crashes in 2023 compared to 61 in 2022.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-12-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes on wet road surfaces increased by 13.9% from 202 in December 2022 to 230 in December 2023, while crashes on dry surfaces decreased. The number of crashes during rainy conditions was identical at 157 for both periods, but collisions in cloudy weather increased from 62 to 105. Crashes in daylight were nearly unchanged (448 vs 444), while those in lighted, dark conditions decreased from 385 to 354.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-12-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-12-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-12-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The most common vehicle types involved in crashes remained consistent, with Passenger Cars, (Sport) Utility Vehicles, and Pickup Trucks being the top three in both December 2023 and 2022. The ranking of the top three vehicle makes involved in crashes also did not change. Toyota (221 vehicles), Honda (172), and Ford (149) led in December 2023, reflecting a slight decrease in counts from the prior year's totals of 244, 176, and 150, respectively.
Top Vehicle Makes (1,634 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-12-01 to 2023-12-31 · 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: 2023-12-01 through 2023-12-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2023-12-01 through 2023-12-31 (31 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 944
- Total persons involved: 1,677
- Total vehicles involved: 1,634
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 2023." Published September 9, 2026. Reporting period: 2023-12-01 to 2023-12-31. 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-2023-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: 2023-12-01 – 2023-12-31
Generated: September 9, 2026 · All rights reserved