ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · TEWKSBURY, MA · DECEMBER 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/december-2022-report
Monthly Traffic Safety Analysis
76 CRASHES IN
TEWKSBURY, MA
DECEMBER 2022
Total crashes in TEWKSBURY, MA increased from 56 in December 2021 to 76 in December 2022, representing a 35.71% increase year-over-year. This period also saw a 100% increase in hit-and-run crashes, rising from 3 to 6 incidents. Overall, there was an increase in total injuries from 14 to 15, while total fatalities remained constant at 1.
76
▲ 35.7%was 56
Total Crash Events
1
Persons Killed
15
▲ 7.1%was 14
Persons Injured
6
▲ 100.0%was 3
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a significant increase in crash incidents year-over-year, with total crashes rising by 35.71% from 56 in December 2021 to 76 in December 2022. This represents an increase of 20 crashes. Total injuries also saw a slight increase of 7.14%, from 14 to 15, while total fatalities remained unchanged.
6
Hit-and-Run Crashes — December 2022
▲ 100.0% vs prior (3)
Hit-and-run crashes increased significantly year-over-year, rising from 3 incidents in December 2021 to 6 incidents in December 2022, a 100% increase. The hit-and-run rate also increased from 5.4% to 7.9%, indicating an upward trend in such incidents.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Motorists Killed
0
Pedestrians Injured
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Thursday in December 2021 (13 crashes) to Friday in December 2022 (18 crashes), marking a 125% increase in crashes on Fridays. The peak hour remained 4 PM in both periods, with crash counts increasing from 7 to 11. Notably, crashes on Tuesdays decreased significantly from 7 to 2, a 71.4% reduction.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes remained constant at 1 in both periods, though the fatal crash rate decreased slightly from 1.79% to 1.32% due to the overall increase in crashes. Serious injury crashes increased from 0 in December 2021 to 1 in December 2022. Minor injury crashes increased by 80% from 5 to 9, while possible injury crashes decreased by 25% from 4 to 3.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'Failed to yield right of way' increased by 8 incidents, from 5 in December 2021 to 13 in December 2022. Similarly, 'Inattention' increased by 8 incidents, rising from 4 to 12. Conversely, crashes related to 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased by 3 incidents, from 5 to 2.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased by 19 incidents, from 30 to 49. Crashes during 'Dark - lighted roadway' conditions increased by 10 incidents, from 13 to 23. There was also an increase of 6 crashes on 'Snow' road surfaces, which were not reported in the prior period, while crashes on 'Ice' road surfaces decreased by 5 incidents.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased from 125 to 162 year-over-year. The largest increases in age group representation were among persons aged 65+ (from 13 to 23) and 26-34 (from 28 to 37). Toyota vehicles were involved in 8 more crashes, rising from 14 to 22, while Honda involvement decreased by 1, from 19 to 18.
Top Vehicle Makes (135 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Vehicle unit records
8 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (148 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
There was a notable shift in crash distribution towards higher speed zones, with crashes in 35 mph zones increasing by 12 incidents (from 19 to 31) and 65 mph zones increasing by 4 incidents (from 5 to 9). Conversely, crashes in 30 mph zones decreased by 7 incidents, from 21 to 14. The single fatal crash shifted from a 30 mph zone in December 2021 to a 35 mph zone in December 2022.
Fatal crashes by zone: 35 mph: 1 of 31 (3.226%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 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: 2022-12-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-12-01 through 2022-12-31 (31 days)
- Geographic scope: TEWKSBURY, MA
- Total crash records analyzed: 76
- Total persons involved: 162
- Total vehicles involved: 135
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: December 2022." Published June 21, 2026. Reporting period: 2022-12-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/tewksbury/december-2022-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: 2022-12-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved