ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MONTGOMERY, MD · MAY 2021
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-2021-report
Monthly Traffic Safety Analysis
793 CRASHES IN
MONTGOMERY, MD
MAY 2021
In May 2021, Montgomery County recorded 793 total crashes, a 72.8% increase from the 459 crashes reported in May 2020. This year-over-year comparison shows a significant rise in overall crash volume, accompanied by a 79.5% increase in total injuries from 156 to 280. While total fatalities decreased from two to one, the most notable shift was the substantial increase in the total number of crashes.
793
▲ 72.8%was 459
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
280
▲ 79.5%was 156
Persons Injured
174
▲ 95.5%was 89
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 6 crashes with unreported severity are not shown in the severity breakdown.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-05-01 to 2021-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year data indicates a significant upward trend in traffic crashes in Montgomery County. Total crashes rose by 72.8%, from 459 in May 2020 to 793 in May 2021. This increase was mirrored in the number of injuries, which climbed by 79.5% from 156 to 280, while fatalities decreased from two to one.
174
Hit-and-Run Crashes — May 2021
▲ 95.5% vs prior (89)
Hit-and-run incidents increased significantly year-over-year. The total count of hit-and-run crashes rose by 95.5%, from 89 in May 2020 to 174 in May 2021. The hit-and-run rate, which represents the proportion of all crashes that were hit-and-runs, also trended upward, increasing from 19.4% to 21.9%.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
20
Pedestrians Injured
16
Cyclists Injured
244
Motorists Injured
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-05-01 to 2021-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Temporal patterns shifted between May 2020 and May 2021. The day with the most crashes changed from Friday (110 crashes) in the prior period to Saturday (138 crashes) in the current period. The peak hour for crashes also shifted earlier, from 5 p.m. (36 crashes) in 2020 to 3 p.m. (68 crashes) in 2021, which represents an 88.9% increase in crashes during that specific hour.
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-05-01 to 2021-05-31 · Crash date field aggregated by weekday
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-05-01 to 2021-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the total number of crashes increased, the severity distribution remained largely consistent year-over-year. The fatal crash rate decreased from 0.44% in May 2020 to 0.13% in May 2021, with one fatal crash recorded compared to two in the prior year. The proportion of crashes involving serious injuries (2.3% vs 2.2%), minor injuries (11.5% vs 11.5%), and possible injuries (15.4% vs 15.3%) saw minimal change.
Outcome by Severity (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-05-01 to 2021-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-05-01 to 2021-05-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent year-over-year, though their counts increased significantly. The top factor in both periods was 'RAIN, SNOW, WET,' with the number of associated crashes doubling from 26 in May 2020 to 52 in May 2021. Similarly, crashes citing 'N/A, WET' as a factor increased from 24 to 35. The share of total crashes attributed to the top factor, 'RAIN, SNOW, WET,' increased slightly from a 5.7% share to a 6.6% share.
Officer-Reported Primary Contributing Cause
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-05-01 to 2021-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes across various environmental conditions remained largely unchanged year-over-year. In May 2021, 71.1% of crashes occurred in clear weather, compared to 68.4% in May 2020. Similarly, 73.0% of crashes happened in daylight, a slight increase from 70.8% in the prior year. While the absolute number of crashes on wet roads increased from 71 to 113, their share of the total decreased slightly from 15.5% to 14.2%.
Weather
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-05-01 to 2021-05-31 · Weather condition at time of crash
Lighting
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-05-01 to 2021-05-31 · Lighting condition field
Road Surface
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-05-01 to 2021-05-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained Toyota, Honda, and Ford, though their order shifted. Toyota maintained its top position, with vehicle involvements increasing from 119 to 220. Honda moved from third to second place, with its count rising from 80 to 163, while Ford moved to third, increasing from 83 to 126 vehicles. Passenger cars were the most common vehicle type in both periods, with their count increasing from 548 in May 2020 to 959 in May 2021.
Top Vehicle Makes (1,346 vehicles)
Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2021-05-01 to 2021-05-31 · 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: 2021-05-01 through 2021-05-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2021-05-01 through 2021-05-31 (31 days)
- Geographic scope: montgomery, MD
- Total crash records analyzed: 793
- Total persons involved: 1,382
- Total vehicles involved: 1,346
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 2021." Published September 9, 2026. Reporting period: 2021-05-01 to 2021-05-31. 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-2021-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: 2021-05-01 – 2021-05-31
Generated: September 9, 2026 · All rights reserved