Monthly Traffic Safety Analysis

44 CRASHES IN
TEWKSBURY, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

In March 2023, Tewksbury experienced 44 crashes, a decrease from 57 crashes in March 2022. This represents a 22.8% reduction in total crashes year-over-year. The most notable shift was the decrease in total injuries, which fell by 25% from 12 to 9.

44

-22.8%was 57

Total Crash Events

0

Persons Killed

9

-25.0%was 12

Persons Injured

4

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. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Tewksbury showed a downward trend year-over-year, with total crashes decreasing from 57 in March 2022 to 44 in March 2023. This marks a 22.8% reduction in crashes. Similarly, total injuries decreased by 25%, from 12 to 9.

4

Hit-and-Run Crashes — March 2023

0.0% vs prior (4)

The number of hit-and-run crashes remained constant at 4 in both March 2022 and March 2023. However, the hit-and-run rate increased from 7% of total crashes in March 2022 to 9.1% in March 2023. This increase in rate occurred despite the absolute number of hit-and-run incidents staying the same, due to a decrease in overall crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

9

Motorists Injured

Prior: 12-25.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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 year-over-year. In March 2023, Tuesday became the peak day for crashes with 12 incidents, compared to Thursday being the peak day with 15 crashes in March 2022. The peak crash hour also changed, moving from 7 AM with 9 crashes in March 2022 to 12 PM with 6 crashes in March 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either March 2022 or March 2023. Total injuries decreased from 12 to 9 year-over-year, with serious injuries (code A) dropping from 1 to 0. Minor injuries (code B) remained stable at 5, while possible injuries (code C) decreased from 4 to 2.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes11.4%
0.0%prior 5
Possible Injury2possible injury crashes4.5%
-50.0%prior 4
No Injury35no injury crashes79.5%
-22.2%prior 45

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Inattention' crashes decreased by 7, from 13 in March 2022 to 6 in March 2023. Crashes due to 'Failed to yield right of way' also decreased by 3, from 7 to 4. Conversely, 'Driving too fast for conditions' increased from 0 to 2 crashes year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving18 (40.9%)0.0%prior 18
Inattention6 (13.6%)-53.8%prior 13
Failed to yield right of way4 (9.1%)-42.9%prior 7
Followed too closely2 (4.5%)
Driving too fast for conditions2 (4.5%)
Disregarded traffic signs, signals, road markings2 (4.5%)
Other improper action2 (4.5%)
Failure to keep in proper lane or running off road1 (2.3%)
Exceeded authorized speed limit1 (2.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring on dry road surfaces decreased from 73.7% (42 of 57) in March 2022 to 63.6% (28 of 44) in March 2023. Crashes on snow-covered roads increased from 3 to 7, while crashes on icy roads decreased from 5 to 0. Daylight crashes decreased from 44 to 32, while crashes in dark-lighted roadway conditions slightly increased from 11 to 12.

Weather

Clear23 (52.3%)
-25.8%prior 31
Snow5 (11.4%)
Cloudy5 (11.4%)
-44.4%prior 9
Rain4 (9.1%)
Snow/Sleet, hail (freezing rain or drizzle)2 (4.5%)
Clear/Cloudy2 (4.5%)
Cloudy/Snow1 (2.3%)
Snow/Blowing sand, snow1 (2.3%)
Cloudy/Rain1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash

Lighting

Daylight32 (72.7%)
-27.3%prior 44
Dark - lighted roadway12 (27.3%)
9.1%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field

Road Surface

Dry28 (63.6%)
-33.3%prior 42
Wet9 (20.5%)
28.6%prior 7
Snow7 (15.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 102 in March 2022 to 86 in March 2023. There was a notable decrease in persons aged 26-34 involved in crashes, from 18 to 10. The top vehicle make involved shifted, with FORD moving from 9 vehicles (5th rank) to 15 vehicles (1st rank), while TOYOTA dropped from 17 vehicles (1st rank) to 11 vehicles (3rd rank).

Top Vehicle Makes (86 vehicles)

1
FORD15 (17.4%)
66.7%prior 9
2
HONDA12 (14%)
0.0%prior 12
3
TOYOTA11 (12.8%)
-35.3%prior 17
4
CHEVROLET7 (8.1%)
-30.0%prior 10
5
NISSAN6 (7%)
-33.3%prior 9
6
SUBARU5 (5.8%)
0.0%prior 5
7
GMC3 (3.5%)
8
VOLKSWAGEN3 (3.5%)
9
HYUNDAI3 (3.5%)
10
JEEP2 (2.3%)
-60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records

8 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (95 persons with recorded sex)

Male51 (53.7%)
-19.0%prior 63
Female44 (46.3%)
12.8%prior 39

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 35 mph speed zones saw the largest reduction, decreasing from 26 in March 2022 to 17 in March 2023. Crashes in 30 mph zones also decreased from 13 to 10. There were no fatal crashes recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-03-01 through 2023-03-31 (31 days)
  • Geographic scope: TEWKSBURY, MA
  • Total crash records analyzed: 44
  • Total persons involved: 103
  • Total vehicles involved: 86

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: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/tewksbury/march-2023-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

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Tewksbury, MA Crash Report — March 2023 | ThatCarHitMe.com