ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MILFORD, MA · AUGUST 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/massachusetts/milford/august-2023-report
Monthly Traffic Safety Analysis
104 CRASHES IN
MILFORD, MA
AUGUST 2023
In August 2023, Milford experienced 104 crashes, a notable increase from the 70 crashes reported in August 2022. This represents a 48.57% rise in total crashes year-over-year. The most significant shift was in total injuries, which increased by 78.57% from 14 to 25.
104
▲ 48.6%was 70
Total Crash Events
0
Persons Killed
25
▲ 78.6%was 14
Persons Injured
11
▲ 83.3%was 6
Hit-and-Run Crashes
Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in Milford showed a significant upward trend year-over-year. Total crashes increased by 48.57%, rising from 70 in August 2022 to 104 in August 2023. Concurrently, the number of persons injured in crashes rose from 14 to 25, marking a 78.57% increase.
11
Hit-and-Run Crashes — August 2023
▲ 83.3% vs prior (6)
Hit-and-run crashes increased significantly year-over-year, rising from 6 incidents in August 2022 to 11 in August 2023. This represents an 83.33% increase in the count of hit-and-run crashes. Consequently, the hit-and-run rate also increased from 8.6% to 10.6% of total crashes.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
23
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · 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 year-over-year. In August 2023, the peak day for crashes was Saturday with 19 incidents, whereas in August 2022, Tuesday was the peak day with 17 crashes. The peak hour also changed, moving from 3 p.m. with 8 crashes in the prior period to 4 p.m. with 12 crashes in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While there were no fatalities in either period, the number of total injuries increased substantially from 14 in August 2022 to 25 in August 2023, a 78.57% rise. Serious injuries decreased from 3 (4.3% share) to 2 (1.9% share), while minor injuries increased from 6 (8.6% share) to 10 (9.6% share). Possible injuries also saw an increase from 3 (4.3% share) to 5 (4.8% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Most severe injury per crash record
Top Contributing Factors
Contributing factors saw notable shifts in crash counts year-over-year. 'No improper driving' crashes increased from 9 to 27, a 200% rise in count, becoming the top factor. Crashes attributed to 'Followed too closely' more than doubled, increasing from 5 to 11, a 120% increase in count. 'Failed to yield right of way' crashes also increased from 9 to 14, a 55.56% increase in count, while 'Inattention' crashes rose from 19 to 22, a 15.79% increase in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring in clear weather remained dominant, with 82 crashes in clear conditions in August 2023 compared to 54 in August 2022. Crashes on dry road surfaces increased from 64 to 95, while those on wet surfaces increased from 6 to 9. Daylight conditions continued to account for the majority of crashes, rising from 62 to 87 year-over-year.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 133 in August 2022 to 193 in August 2023, representing a 45.11% rise. Toyota remained the top make involved, increasing from 26 to 33 vehicles. Ford also saw an increase from 18 to 26 vehicles, while Chevrolet rose from 12 to 22, and Honda decreased from 14 to 9.
Top Vehicle Makes (193 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Vehicle unit records
38 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (189 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone significantly increased from 41 in August 2022 to 68 in August 2023, a 65.85% rise in count. The 5 mph zone also saw an increase from 5 crashes to 9, an 80% rise in count. Crashes in the 65 mph zone increased from 2 to 5, a 150% rise in count, while fatal rates remained at 0 across all speed zones in both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · 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: 2023-08-01 through 2023-08-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-08-01 through 2023-08-31 (31 days)
- Geographic scope: MILFORD, MA
- Total crash records analyzed: 104
- Total persons involved: 229
- Total vehicles involved: 193
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: August 2023." Published June 21, 2026. Reporting period: 2023-08-01 to 2023-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/milford/august-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: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-08-01 – 2023-08-31
Generated: June 21, 2026 · All rights reserved