ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · APRIL 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/april-2023-report
Monthly Traffic Safety Analysis
864 CRASHES IN
MONTGOMERY, MD
APRIL 2023
In April 2023, Montgomery County recorded 864 total crashes, a 6.7% increase from the 810 crashes reported in April 2022. While overall crashes and injuries rose, the number of traffic fatalities decreased by 50%, falling from 4 to 2 year-over-year. The most notable shift was the increase in serious injury crashes, which rose from 11 to 20.
864
▲ 6.7%was 810
Total Crash Events
2
▼ -50.0%was 4
Persons Killed
293
▲ 8.5%was 270
Persons Injured
204
▲ 27.5%was 160
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. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year data for April indicates a rising trend in the total number of traffic collisions in Montgomery County. Crashes increased by 6.7%, from 810 in April 2022 to 864 in April 2023. Similarly, the number of people injured in these incidents rose by 8.5% from 270 to 293, while total fatalities decreased from 4 to 2.
204
Hit-and-Run Crashes — April 2023
▲ 27.5% vs prior (160)
Hit-and-run incidents increased significantly in April 2023 compared to the previous year. The total number of hit-and-run crashes rose by 27.5%, from 160 in April 2022 to 204 in April 2023. Consequently, the hit-and-run rate, representing the proportion of all crashes that were hit-and-runs, climbed from 19.8% to 23.6%.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
0
Other Killed
32
Pedestrians Injured
13
Cyclists Injured
244
Motorists Injured
4
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-04-01 to 2023-04-30 · 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 minor shifts between April 2022 and April 2023. The peak day for crashes moved from Friday (163 crashes) in the prior period to Saturday (161 crashes) in the current period. The busiest time of day also shifted an hour later, from the 3 p.m. hour in 2022 (66 crashes) to the 4 p.m. hour in 2023 (70 crashes).
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes increased, the severity profile shifted year-over-year. The number of fatal crashes decreased from 4 in April 2022 to 2 in April 2023, with their share of all crashes falling from 0.5% to 0.2%. Conversely, serious injury crashes increased in both count, from 11 to 20, and proportion, from 1.4% to 2.3% of all crashes. The share of crashes resulting in minor or possible injuries remained stable.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors cited in crashes remained consistent, with weather-related issues being most common in both periods. The top factor, 'RAIN, SNOW, WET', was cited in 43 crashes in April 2023, a decrease from 55 in the prior year. The second most common factor, 'N/A, WET', also saw its count decline from 38 to 31. Crashes attributed to 'BACKUP DUE TO REGULAR CONGESTION, N/A' increased from 6 to 9.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in clear weather constituted the majority in both periods, and their proportion increased in April 2023. Crashes during clear weather rose from 553 (68.3% of total) in 2022 to 637 (73.7% of total) in 2023. Correspondingly, crashes occurring in rain decreased from 111 to 97. Regarding lighting, crashes in daylight remained the dominant condition, while collisions on dark but lighted roads increased from 161 to 178.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field
Vehicles & Demographics
The composition of vehicles involved in crashes remained largely unchanged. Passenger cars and (Sport) Utility Vehicles were the most common vehicle types in both periods, with their counts increasing in line with the overall rise in crashes. The top three most-involved vehicle makes were Toyota, Honda, and Ford in both April 2022 and April 2023, maintaining their respective rankings.
Top Vehicle Makes (1,525 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2023-04-01 through 2023-04-30 (30 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 864
- Total persons involved: 1,577
- Total vehicles involved: 1,525
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: April 2023." Published September 9, 2026. Reporting period: 2023-04-01 to 2023-04-30. 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/april-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: 2023-04-01 – 2023-04-30
Generated: September 9, 2026 · All rights reserved