ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · TEWKSBURY, 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/tewksbury/2022-annual-report
Yearly Traffic Safety Analysis
646 CRASHES IN
TEWKSBURY, MA
2022
In 2022, Tewksbury recorded 646 vehicle crashes, a 23.5% increase from the 523 crashes reported in 2021. While total fatalities decreased from 5 to 2 year-over-year, the number of reported injuries rose from 123 to 149. One of the most significant shifts was in hit-and-run incidents, which increased by nearly 69%, from 32 in 2021 to 54 in 2022.
646
▲ 23.5%was 523
Total Crash Events
2
▼ -60.0%was 5
Persons Killed
149
▲ 21.1%was 123
Persons Injured
54
▲ 68.8%was 32
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. 19 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 Tewksbury indicates a rising trend in 2022 compared to the previous year. Total crashes increased by 23.5%, from 523 in 2021 to 646 in 2022. The number of people injured in these incidents grew by 21.1%, while the number of fatalities decreased from 5 to 2.
54
Hit-and-Run Crashes — 2022
▲ 68.8% vs prior (32)
Hit-and-run incidents increased significantly in 2022 compared to the prior year. The total number of hit-and-run crashes rose by 68.8%, from 32 in 2021 to 54 in 2022. This represents a clear upward trend, as the rate of hit-and-runs as a percentage of all crashes also increased from 6.1% in 2021 to 8.4% in 2022.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
5
Pedestrians Injured
5
Cyclists Injured
139
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 higher volumes in 2022. Friday was the peak day for crashes in both 2022 (118 incidents) and 2021 (86 incidents). Similarly, the 3 PM hour was the most frequent time for crashes in both periods, with 63 crashes in 2022 and 52 in 2021. Crashes during the morning commute hours of 7 AM and 8 AM saw a notable increase, rising from a combined 48 incidents in 2021 to 69 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
In 2022, there was a decrease in the most severe outcomes, with fatal crashes dropping from 5 in 2021 to 2 in 2022, and the corresponding fatal crash rate declining from 0.96% to 0.31%. However, the number of crashes resulting in serious injuries more than tripled, increasing from 2 in 2021 to 7 in 2022. Overall, the proportion of crashes involving any level of injury (serious, minor, or possible) saw a slight increase from 17.2% of all crashes in 2021 to 18.3% 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
The leading contributing factors cited in crashes remained consistent between 2021 and 2022, though their frequency generally increased. 'Inattention' was the top driver-related factor in both years, with the count of such incidents rising by 47%, from 83 in 2021 to 122 in 2022. Crashes attributed to 'Failed to yield right of way' also saw a significant jump, with the count increasing by 57% from 54 to 85. In contrast, incidents where 'Followed too closely' was a factor decreased by 27%, from a count of 48 in 2021 to 35 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 unchanged between 2021 and 2022. In both years, the majority of incidents occurred in clear weather (approximately 70% of all crashes) and on dry road surfaces (approximately 77%). Crashes during daylight hours also accounted for a consistent share, representing 68.1% of incidents in 2022 compared to 67.3% in 2021. There was no significant proportional shift to suggest that changes in weather, lighting, or road surface conditions were a primary driver of the overall increase in crashes.
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 makes of vehicles involved in crashes saw a minor shift in rankings between the two periods. In 2022, Toyota became the most frequently involved make with 180 vehicles, surpassing Honda (163), which was the top make in 2021 with 139 vehicles. Analysis of persons involved in crashes shows a notable increase in the 55-64 age group, whose share of total persons grew from 9.3% in 2021 to 11.9% in 2022. Conversely, the 26-34 age group, while still representing a large portion of those involved, saw its share decrease from 18.4% to 15.9%.
Top Vehicle Makes (1,180 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
107 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,273 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 distribution of crashes across different speed zones shifted in 2022, with the bulk of the year-over-year increase occurring in 35 mph zones, where crashes rose by 51% from 174 in 2021 to 263 in 2022. In contrast, crashes in 65 mph zones saw a slight decrease from 80 to 75 incidents. Fatal crashes were less concentrated in high-speed zones in 2022; while 2021 saw 3 fatalities in the 65 mph zone, 2022 recorded one fatality in a 65 mph zone and one in a 35 mph zone.
Fatal crashes by zone: 35 mph: 1 of 263 (0.38%) · 65 mph: 1 of 75 (1.333%)
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: TEWKSBURY, MA
- Total crash records analyzed: 646
- Total persons involved: 1,414
- Total vehicles involved: 1,180
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). "TEWKSBURY, 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/tewksbury/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