ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MILFORD, MA · 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/massachusetts/milford/2022-annual-report
Yearly Traffic Safety Analysis
969 CRASHES IN
MILFORD, MA
2022
In 2022, Milford recorded 969 total crashes, a 2.5% decrease from the 994 crashes reported in 2021. While overall crashes and injuries declined, the most significant year-over-year change was a 380% increase in hit-and-run incidents, which rose from 10 in 2021 to 48 in 2022.
969
▼ -2.5%was 994
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
181
▼ -22.6%was 234
Persons Injured
48
▲ 380.0%was 10
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. 63 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data for Milford shows a slight downward trend year-over-year. Total crashes decreased by 2.5%, from 994 in 2021 to 969 in 2022. This trend was accompanied by a 22.6% reduction in total injuries and a 50% drop in fatalities, from two deaths in 2021 to one in 2022.
48
Hit-and-Run Crashes — 2022
▲ 380.0% vs prior (10)
Hit-and-run crashes saw a significant increase in Milford from 2021 to 2022. The number of hit-and-run incidents rose from 10 to 48, representing a 380% increase in count. As a result, the hit-and-run rate, or the percentage of total crashes that were hit-and-runs, climbed from 1.0% in 2021 to 5.0% in 2022.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
13
Pedestrians Injured
4
Cyclists Injured
164
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes in Milford shifted between 2021 and 2022. The peak day for collisions moved from Saturday (164 crashes) in the prior year to Thursday (151 crashes) in the current year. Similarly, the peak hour for crashes shifted from 3 PM (92 crashes) in 2021 to the 5 PM evening commute hour (93 crashes) in 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes in Milford lessened from 2021 to 2022. The number of fatal crashes dropped from two to one, lowering the fatal crash rate from 0.2% to 0.1% of all incidents. The proportion of crashes resulting in any level of injury decreased from 17.5% of all crashes in 2021 to 15.1% in 2022. Correspondingly, the share of no-injury crashes increased from 73.8% to 78.2%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The primary contributing factors to crashes in Milford remained consistent between 2021 and 2022, with 'Inattention' being the most cited factor in both years. The count of crashes attributed to inattention decreased by 14.2%, from 260 in 2021 to 223 in 2022. Crashes involving 'Failed to yield right of way' also saw a decline in count from 129 to 120. Conversely, crashes attributed to 'Followed too closely' increased in count by 11.8%, from 68 incidents in 2021 to 76 in 2022.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions in Milford were broadly similar year-over-year. In both 2021 and 2022, the majority of crashes occurred in clear weather and during daylight hours. The proportion of crashes on dry road surfaces was identical in both periods at 80.5% of all incidents. Crashes on wet roads saw a proportional decrease, accounting for 15.5% of crashes in 2021 and 13.1% in 2022.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in Milford crashes were Toyota, Ford, and Honda in both 2021 and 2022. The number of Toyotas and Fords involved in crashes decreased, while the number of Hondas increased from 177 to 194. Regarding persons involved in collisions, the 26-34 age group was the most frequently involved demographic in both years, though its count fell from 376 to 346. The 45-54 age group's representation increased, replacing the 21-25 age group as the third most-involved cohort in 2022.
Top Vehicle Makes (1,815 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
318 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,804 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The 30 mph speed zone was the most common location for crashes in both periods, with the number of incidents in this zone increasing from 614 in 2021 to 640 in 2022. A notable shift occurred in the location of fatal crashes; the two fatalities in 2021 occurred in a 65 mph zone, while the single fatality in 2022 occurred in a 30 mph zone. Crashes in the 65 mph zone saw an overall decrease in count from 75 to 64 year-over-year.
Fatal crashes by zone: 30 mph: 1 of 640 (0.156%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Posted speed limit at crash location
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly 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: Arcgis_yearly Open Data API (SoQL queries)
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: MILFORD, MA
- Total crash records analyzed: 969
- Total persons involved: 2,133
- Total vehicles involved: 1,815
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). "MILFORD, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/milford/2022-annual-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: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved