ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · TOWNSEND, 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/townsend/2022-annual-report
Yearly Traffic Safety Analysis
160 CRASHES IN
TOWNSEND, MA
2022
In Townsend, MA, total traffic crashes increased by 26.0% from 127 in 2021 to 160 in 2022. This increase was accompanied by a rise in total injuries from 26 to 36. The most significant year-over-year change was the occurrence of two fatal crashes in 2022, whereas there were no fatal crashes recorded in the prior year.
160
▲ 26.0%was 127
Total Crash Events
2
Persons Killed
36
▲ 38.5%was 26
Persons Injured
1
▼ -66.7%was 3
Hit-and-Run Crashes
Note: "Persons Killed" (2) 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. 7 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
The overall trend in traffic incidents shows a notable increase year-over-year. Total crashes rose from 127 to 160, while the number of people injured increased by 38.5% from 26 to 36. Most critically, traffic fatalities increased from zero in 2021 to two in 2022, indicating a worsening of crash outcomes.
1
Hit-and-Run Crashes — 2022
▼ -66.7% vs prior (3)
The number and rate of hit-and-run incidents decreased from 2021 to 2022. The total count of hit-and-run crashes fell from 3 to 1. Correspondingly, the hit-and-run rate dropped from 2.4% of all crashes in 2021 to 0.6% in 2022.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
34
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 daily and hourly crash patterns showed some consistency and some shifts between the two years. The evening commute hour of 5 p.m. remained the peak time for crashes in both 2022 (17 crashes) and 2021 (20 crashes). However, the peak day for crashes expanded; while Tuesday was a high-frequency day in both years (27 crashes in 2021, 29 in 2022), Friday also emerged as a peak day in 2022 with 29 crashes, up from 18 the previous year.
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
Crash severity worsened in 2022 compared to 2021. The city recorded two fatal crashes in 2022, representing 1.3% of all incidents, up from zero fatal crashes in the prior year. The number of serious injury crashes increased from 4 to 6, and the number of possible injury crashes more than doubled from 4 to 9. Consequently, the share of crashes involving no injuries decreased from 81.9% in 2021 to 78.8% in 2022.
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
Inattention was the leading reported contributing factor in both periods, with its count increasing by 88.2% from 17 crashes in 2021 to 32 crashes in 2022. The count of crashes attributed to 'Failure to keep in proper lane' doubled from 6 to 12, and incidents involving fatigued or asleep drivers tripled from 2 to 6. Conversely, crashes involving an erratic or reckless driver were halved, decreasing from a count of 10 in 2021 to 5 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
The distribution of crashes across different environmental conditions remained largely stable year-over-year. In both 2022 and 2021, the majority of incidents occurred in daylight (67.5% and 59.1%, respectively) and on dry roads (75.6% and 74.8%, respectively). There was no significant shift in the proportion of crashes occurring during adverse weather or poor lighting conditions between the two periods.
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 vehicle makes involved in crashes, Ford and Toyota, remained consistent, though the number of Fords involved increased from 31 to 50. There was a notable demographic shift in persons involved in crashes; the count for the 65+ age group grew from 32 to 52, making it the largest group in 2022. In contrast, involvement for the 16-20 age group decreased from 41 to 30.
Top Vehicle Makes (246 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
23 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (282 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
Year-over-year, the largest increase in crash volume occurred in 35 mph zones, which saw incidents rise from 29 to 44. Crashes also increased in 25 mph zones (from 19 to 24) and 30 mph zones (from 21 to 25). Most significantly, the two fatal crashes recorded in 2022 occurred in 35 mph and 45 mph speed zones, where no fatalities had been reported the previous year.
Fatal crashes by zone: 35 mph: 1 of 44 (2.273%) · 45 mph: 1 of 15 (6.667%)
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: TOWNSEND, MA
- Total crash records analyzed: 160
- Total persons involved: 313
- Total vehicles involved: 246
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). "TOWNSEND, 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/townsend/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