ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · TEWKSBURY, MA · AUGUST 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/august-2022-report
Monthly Traffic Safety Analysis
60 CRASHES IN
TEWKSBURY, MA
AUGUST 2022
Total crashes in TEWKSBURY increased by 50% from 40 in August 2021 to 60 in August 2022. This period saw a significant decrease in total fatalities, dropping from 1 in the prior year to 0 in the current year. Overall injuries also rose from 11 to 15 year-over-year.
60
▲ 50.0%was 40
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
15
▲ 36.4%was 11
Persons Injured
6
▲ 100.0%was 3
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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend for crashes in TEWKSBURY shows a notable increase year-over-year, with total crashes rising by 50% from 40 in August 2021 to 60 in August 2022. This upward trend in crash incidents was accompanied by an increase in total injuries, which went from 11 to 15.
6
Hit-and-Run Crashes — August 2022
▲ 100.0% vs prior (3)
Hit-and-run crashes increased from 3 in August 2021 to 6 in August 2022, representing a 100% increase in count. The hit-and-run rate also rose from 7.5% of total crashes in the prior period to 10% in the current period. This indicates an upward trend in hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
14
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two periods. The peak day for crashes moved from Wednesday with 11 incidents in August 2021 to Tuesday with 14 incidents in August 2022. Similarly, the peak hour for crashes changed from 4 PM with 5 incidents in the prior period to 3 PM with 10 incidents in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes decreased from 1 in August 2021 to 0 in August 2022, resulting in a fatal crash rate drop from 2.5% to 0%. While minor injury crashes decreased slightly from 6 to 5, serious injury crashes increased from 0 to 1. The proportion of crashes resulting in any injury (serious, minor, or possible) decreased from 25% (10 out of 40) in the prior period to 20% (12 out of 60) in the current period.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, "Inattention" crashes increased by 62.5% in count, rising from 8 to 13. "Failed to yield right of way" saw a substantial increase of 166.7% in count, going from 3 to 8 crashes. "No improper driving" remained constant at 13 crashes in both periods, while "Followed too closely" increased by 50% in count, from 2 to 3 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 32 to 50 year-over-year, while cloudy conditions saw a slight increase from 6 to 7 crashes. Daylight crashes rose from 32 to 44, and crashes in dark-lighted roadway conditions increased from 2 to 9. Crashes on dry road surfaces increased from 36 to 55, and wet road surface crashes increased from 3 to 4.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 68 to 115 year-over-year. Honda-involved crashes saw a significant increase from 7 to 25, while Toyota-involved crashes slightly decreased from 14 to 13. Regarding age distribution, crashes involving individuals in the 16-20 age group more than doubled from 9 to 20, and those in the 26-34 age group also significantly increased from 9 to 24.
Top Vehicle Makes (115 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (113 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 35 mph speed zones increased from 11 to 21 year-over-year, and those in 65 mph zones rose from 4 to 9. Conversely, crashes in 30 mph zones decreased from 9 to 7. There was a decrease in fatal crashes within the 25 mph speed zone, going from 1 in the prior period to 0 in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · 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: 2022-08-01 through 2022-08-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-08-01 through 2022-08-31 (31 days)
- Geographic scope: TEWKSBURY, MA
- Total crash records analyzed: 60
- Total persons involved: 135
- Total vehicles involved: 115
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: August 2022." Published June 21, 2026. Reporting period: 2022-08-01 to 2022-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/tewksbury/august-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: 2022-08-01 – 2022-08-31
Generated: June 21, 2026 · All rights reserved