ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ACUSHNET, MA · 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/acushnet/2023-annual-report
Yearly Traffic Safety Analysis
146 CRASHES IN
ACUSHNET, MA
2023
In Acushnet, total traffic crashes increased by 15% from 127 in 2022 to 146 in 2023. While the number of fatal crashes dropped from one to zero, the total number of injuries rose by 88.5%, from 26 to 49. The most significant year-over-year shift was the substantial increase in crashes attributed to distracted driving, which grew from 3 incidents in 2022 to 8 in 2023.
146
▲ 15.0%was 127
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
49
▲ 88.5%was 26
Persons Injured
9
▲ 125.0%was 4
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. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety trends in Acushnet showed a negative turn from 2022 to 2023. The total number of crashes rose from 127 to 146, a 15% year-over-year increase. This was accompanied by an 88.5% rise in the number of people injured, increasing from 26 to 49.
9
Hit-and-Run Crashes — 2023
▲ 125.0% vs prior (4)
Hit-and-run incidents increased significantly between 2022 and 2023. The total count of hit-and-run crashes more than doubled, rising from 4 to 9, a 125% increase. Correspondingly, the hit-and-run rate, or the percentage of all crashes that were hit-and-runs, also doubled from 3.1% in 2022 to 6.2% in 2023.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
1
Pedestrians Injured
1
Cyclists Injured
46
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained largely consistent year-over-year. Friday was the peak day for crashes in both 2023 (30 crashes) and 2022 (22 crashes). Similarly, the 5 p.m. hour was the peak time for collisions in both periods, with 14 crashes in 2023 and 16 in 2022. However, there was a notable increase in crashes on Mondays, which rose from 17 in 2022 to 28 in 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While 2023 saw no fatal crashes compared to one in 2022, the overall severity of crashes worsened. The number of persons sustaining minor injuries increased from 14 to 32, and those with serious injuries rose from 2 to 3. Consequently, the proportion of crashes resulting in any level of injury (serious, minor, or possible) increased from 19.7% of all crashes in 2022 to 26.7% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'No improper driving' remained the most common factor listed for crashes in both years, its count remained stable (51 in 2022 vs. 50 in 2023), causing its share of total crashes to drop from 40.2% to 34.2%. The count of crashes attributed to 'Inattention' increased from 16 to 19, and those due to 'Failed to yield right of way' grew from 8 to 11. Most notably, crashes involving a 'Distracted' driver increased by 167%, from 3 incidents in 2022 to 8 in 2023.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes across environmental conditions shifted between the two years. Crashes in daylight conditions increased from 63 to 82, representing a larger share of the total (49.6% in 2022 vs. 56.2% in 2023). Crashes on dry roads also saw an increase in both count and proportion, rising from 95 incidents (74.8% share) to 122 incidents (83.6% share). Notably, crashes in 'Dark - roadway not lighted' conditions more than doubled, increasing from 12 in 2022 to 25 in 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes saw some shifts, with Toyota's involvement increasing from 26 to 45 vehicles and Ford's from 14 to 27. The demographic profile of persons involved in crashes also changed, with a significant increase in the '65+' age group, which grew from 10 individuals in 2022 to 47 in 2023. The number of individuals in the '0-15' age group also increased from 16 to 24.
Top Vehicle Makes (227 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
30 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (258 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones remained relatively stable, with the highest number of incidents occurring in 40 mph zones in both 2023 (46 crashes) and 2022 (38 crashes). The single fatal crash recorded in 2022 occurred in a 40 mph zone. In 2023, there were no fatal crashes reported in any speed zone. Crashes in 35 mph zones saw a slight increase from 32 to 34 incidents year-over-year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: ACUSHNET, MA
- Total crash records analyzed: 146
- Total persons involved: 290
- Total vehicles involved: 227
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). "ACUSHNET, MA Crash Intelligence Report: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/acushnet/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved