ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · TAUNTON, 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/taunton/2022-annual-report
Yearly Traffic Safety Analysis
2,163 CRASHES IN
TAUNTON, MA
2022
In 2022, Taunton recorded 2,163 total crashes, a 24.4% increase from the 1,739 crashes reported in 2021. While total fatalities decreased from 4 to 3, the number of reported hit-and-run incidents saw a substantial year-over-year increase, rising from 36 to 164.
2,163
▲ 24.4%was 1,739
Total Crash Events
3
▼ -25.0%was 4
Persons Killed
578
▲ 24.6%was 464
Persons Injured
164
▲ 355.6%was 36
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 141 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 trends in Taunton show a significant year-over-year increase. Total crashes rose by 24.4%, from 1,739 in 2021 to 2,163 in 2022. Similarly, the number of people injured in these incidents increased by 24.6% from 464 to 578, while fatalities saw a slight decrease from 4 to 3.
164
Hit-and-Run Crashes — 2022
▲ 355.6% vs prior (36)
The number of hit-and-run crashes increased dramatically year-over-year, rising from 36 incidents in 2021 to 164 in 2022. This represents a 355.6% increase in the count of such events. Consequently, the hit-and-run rate, or the percentage of all crashes that were hit-and-runs, surged from 2.1% in 2021 to 7.6% in 2022, indicating a strong upward trend.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
9
Pedestrians Injured
8
Cyclists Injured
561
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 temporal patterns of crashes remained broadly consistent year-over-year, though with increased volume. Friday was the peak day for crashes in both 2021 (280 crashes) and 2022 (367 crashes). The peak hour for collisions shifted slightly earlier, from the 5 PM hour in 2021 (153 crashes) to the 4 PM hour in 2022 (197 crashes).
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 overall severity of crashes showed mixed changes between 2021 and 2022. The fatal crash rate decreased from 0.23% to 0.14%, with one fewer fatal crash recorded in 2022 (3) than in 2021 (4). Crashes resulting in serious injuries remained proportionally stable at 1.3% of all incidents in both years, though the count increased from 22 to 29. The share of crashes involving minor injuries increased slightly from 12.3% to 12.7%, while the proportion of no-injury crashes remained steady at approximately 75% of all incidents.
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 leading contributing factors for crashes remained consistent between 2021 and 2022, with 'Inattention' and 'Failed to yield right of way' being the top two improper driving actions in both periods. The number of crashes attributed to inattention increased by 23.7%, from 287 to 355. Incidents involving failure to yield the right of way grew by 31.0% (from 229 to 300), and crashes due to following too closely rose by 59.8% (from 117 to 187). The share of crashes attributed to these top factors remained relatively stable year-over-year.
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 majority of crashes in both periods occurred in clear weather and on dry roads. In 2022, 80.8% of crashes happened on dry road surfaces, a slight decrease from 82.0% in 2021. Crashes during daylight hours accounted for 67.8% of the total in 2022, compared to 65.7% in the prior year. The proportion of crashes occurring under adverse conditions like rain or on wet roads remained relatively unchanged 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 five vehicle makes involved in crashes remained the same in 2022 as in 2021, led by Toyota, Ford, and Honda, with all seeing an increase in total counts. Honda moved from the fourth to the third most common make, surpassing Chevrolet. An analysis of persons involved in crashes shows that the 26-34 age group was the largest demographic in both years, increasing from 675 individuals in 2021 to 916 in 2022. The 35-44 age group saw a notable 35.6% increase in involvement, rising from 558 to 757 persons.
Top Vehicle Makes (3,896 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
399 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (4,251 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
Crashes in 30 mph zones remained the most frequent, increasing from 724 incidents in 2021 to 863 in 2022. There was also a notable 35% increase in crashes within 65 mph zones, which rose from 117 to 158. The location of fatal crashes shifted to higher speed zones; in 2021, three of the four fatalities occurred in 20-25 mph zones, whereas in 2022, all three fatalities occurred in 30-35 mph zones.
Fatal crashes by zone: 30 mph: 1 of 863 (0.116%) · 35 mph: 2 of 278 (0.719%)
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: TAUNTON, MA
- Total crash records analyzed: 2,163
- Total persons involved: 4,705
- Total vehicles involved: 3,896
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). "TAUNTON, 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/taunton/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