ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · MAY 2022
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/may-2022-report
Monthly Traffic Safety Analysis
844 CRASHES IN
MONTGOMERY, MD
MAY 2022
In May 2022, Montgomery County recorded 844 total vehicle crashes, a 6.4% increase from the 793 crashes documented in May 2021. While the number of fatalities remained unchanged at one, the number of fatal crashes doubled from one to two. The most significant shift was a 63.5% increase in the count of crashes where 'Rain, Snow, Wet' conditions were a contributing factor, rising from 52 incidents in the prior year to 85 in the current period.
844
▲ 6.4%was 793
Total Crash Events
1
Persons Killed
291
▲ 3.9%was 280
Persons Injured
179
▲ 2.9%was 174
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. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Montgomery County show an increase year-over-year. Total crashes rose by 6.4%, from 793 in May 2021 to 844 in May 2022. Similarly, the number of people injured in these incidents increased by 3.9%, from 280 to 291, while the number of fatalities held steady at one for both periods.
179
Hit-and-Run Crashes — May 2022
▲ 2.9% vs prior (174)
The number of hit-and-run crashes saw a slight increase, rising from 174 in May 2021 to 179 in May 2022. However, because the total number of crashes grew at a faster pace, the hit-and-run rate as a percentage of all crashes decreased slightly, from 21.9% in the prior period to 21.2% in the current period.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
22
Pedestrians Injured
10
Cyclists Injured
257
Motorists Injured
2
Other Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-05-01 to 2022-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In May 2022, the peak day for crashes was Tuesday with 150 incidents, a change from May 2021 when Saturday was the peak day with 138 crashes. The peak hour for collisions also shifted slightly, moving from the 3 p.m. hour (68 crashes) in the prior year to the 2 p.m. hour (63 crashes) in the current year.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the total number of fatalities was unchanged, the number of fatal crashes increased from one in May 2021 to two in May 2022, causing the fatal crash rate to nearly double from 0.13% to 0.24%. The count of serious injury crashes decreased from 18 to 14. Conversely, crashes involving minor injuries rose from 91 to 97, and possible injury crashes increased from 122 to 133 year-over-year.
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 · 2022-05-01 to 2022-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent, though their counts changed. 'Rain, Snow, Wet' was the top factor in both periods; its count increased by 63.5% from 52 crashes in May 2021 to 85 crashes in May 2022. The second-ranked factor, 'N/A, Wet', also saw its count rise from 35 to 38 incidents. The share of crashes attributed to 'Rain, Snow, Wet' grew from 6.6% to 10.1% of all crashes.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-05-01 to 2022-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
There was a notable increase in crashes occurring during adverse conditions compared to the previous year. Crashes on wet road surfaces increased from 113 to 175, and incidents during rain increased from 98 to 145. Consequently, the proportion of crashes on wet roads grew from 16.8% in May 2021 to 24.7% in May 2022. Lighting conditions remained relatively stable, with daylight crashes accounting for the vast majority in both periods (608 in 2022 vs. 579 in 2021).
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-05-01 to 2022-05-31 · Road surface condition field
Vehicles & Demographics
The ranking of the most common vehicle makes involved in crashes remained stable year-over-year. Toyota, Honda, and Ford were the top three makes in both May 2022 and May 2021. The number of Toyotas involved decreased slightly from 220 to 215, while Hondas increased from 163 to 166 and Fords increased from 126 to 131.
Top Vehicle Makes (1,457 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2022-05-01 to 2022-05-31 · 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: 2022-05-01 through 2022-05-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2022-05-01 through 2022-05-31 (31 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 844
- Total persons involved: 1,504
- Total vehicles involved: 1,457
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: May 2022." Published September 9, 2026. Reporting period: 2022-05-01 to 2022-05-31. 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/may-2022-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: 2022-05-01 – 2022-05-31
Generated: September 9, 2026 · All rights reserved