ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · JUNE 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/june-2023-report
Monthly Traffic Safety Analysis
875 CRASHES IN
MONTGOMERY, MD
JUNE 2023
In June 2023, Montgomery County recorded 875 total vehicle crashes, a 7.2% increase from the 816 crashes documented in June 2022. Despite the rise in total collisions, the most notable year-over-year shift was a significant decrease in fatalities, which dropped from 4 in the prior period to 1 in the current period. Total reported injuries remained unchanged at 312 for both months.
875
▲ 7.2%was 816
Total Crash Events
1
▼ -75.0%was 4
Persons Killed
312
Persons Injured
177
▲ 12.7%was 157
Hit-and-Run Crashes
Note: "Persons Killed" (1) 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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash totals in Montgomery County trended upward in June 2023 compared to the same month in the previous year, increasing by 59 incidents from 816 to 875. While the overall number of crashes grew, the number of people killed in these incidents decreased from 4 to 1. The total number of people injured in crashes was identical across both periods, at 312.
177
Hit-and-Run Crashes — June 2023
▲ 12.7% vs prior (157)
Hit-and-run crashes increased both in total count and as a percentage of all collisions. The number of hit-and-run incidents rose from 157 in June 2022 to 177 in June 2023, a 12.7% increase. The hit-and-run rate also trended upward, climbing from 19.2% of all crashes in the prior period to 20.2% in the current period.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
33
Pedestrians Injured
10
Cyclists Injured
267
Motorists Injured
2
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-06-01 to 2023-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two periods. In June 2023, the peak day for crashes was Friday with 160 incidents, a change from June 2022 when Wednesday was the peak day with 144 crashes. The peak hour also shifted slightly earlier, from 4 PM in the prior year (74 crashes) to 3 PM in the current year (68 crashes).
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Year-over-year, the severity of crashes showed a mixed profile, highlighted by a significant drop in the most severe outcomes. Fatalities decreased from 4 in June 2022 to 1 in June 2023, and the fatal crash rate fell from 0.5% to 0.1% of total crashes. Conversely, crashes involving serious injuries increased from 12 to 17. The proportion of crashes resulting in no injuries grew from 66.8% to 68.6% of all incidents.
Severity is per crash event (most severe injury). 2 fatal crash events resulted in 1 persons killed.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors in both periods were related to wet road conditions. The count of crashes where "RAIN, SNOW, WET" was cited as a factor increased by 75%, from 40 incidents in June 2022 to 70 in June 2023. Similarly, crashes with the factor "N/A, WET" rose from 29 to 42. These two factors maintained their top rankings from the prior year, but their frequency increased notably.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in adverse conditions were more prevalent in June 2023 than in the same month of the prior year. Collisions that took place in the rain increased from 66 to 113, and incidents on wet road surfaces rose from 84 to 137. In contrast, the number of crashes on dry roads (590 vs. 586) and in clear weather (626 vs. 623) remained relatively stable between the two periods.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field
Vehicles & Demographics
The makes of vehicles most frequently involved in crashes remained consistent, with Toyota, Honda, and Ford holding the top three spots in both June 2022 and June 2023. The number of passenger cars involved in collisions increased from 969 to 1,137, reflecting the overall rise in crash volume. The count of sport utility vehicles involved was unchanged at 149 in both periods.
Top Vehicle Makes (1,564 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2023-06-01 through 2023-06-30 (30 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 875
- Total persons involved: 1,617
- Total vehicles involved: 1,564
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: June 2023." Published September 9, 2026. Reporting period: 2023-06-01 to 2023-06-30. 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/june-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: 2023-06-01 – 2023-06-30
Generated: September 9, 2026 · All rights reserved