Monthly Traffic Safety Analysis

29 CRASHES IN
TYNGSBOROUGH, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

In March 2023, Tyngsborough experienced 29 total crashes, an increase from the 22 crashes reported in March 2022, representing a 31.8% rise. A notable year-over-year shift was the increase in hit-and-run crashes, which went from 0 in March 2022 to 3 in March 2023.

29

31.8%was 22

Total Crash Events

0

Persons Killed

9

28.6%was 7

Persons Injured

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. 1 crash with unreported severity is 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, crashes in Tyngsborough increased year-over-year, rising from 22 total crashes in March 2022 to 29 total crashes in March 2023, an increase of 7 crashes or 31.8%. Total injuries also saw an upward trend, increasing from 7 in March 2022 to 9 in March 2023, a 28.6% rise.

3

Hit-and-Run Crashes — March 2023

10.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

9

Motorists Injured

Prior: 728.6%

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 peak day for crashes shifted from Saturday with 6 crashes in March 2022 to Tuesday with 8 crashes in March 2023. Similarly, the peak hour for crashes changed from 10p with 2 crashes in March 2022 to 6p with 4 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 in either March 2022 or March 2023. Minor injuries increased from 5 in March 2022 to 7 in March 2023, while possible injuries remained stable at 1 in both periods. Crashes resulting in no injury increased from 16 to 20 year-over-year.

Outcome by Severity (Crash Events)

Minor Injury7minor injury crashes24.1%
40.0%prior 5
Possible Injury1possible injury crashes3.4%
0.0%prior 1
No Injury20no injury crashes69%
25.0%prior 16

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

The contributing factor 'No improper driving' saw a significant increase in count, rising from 6 crashes in March 2022 to 14 crashes in March 2023. Conversely, 'Inattention' decreased from 7 crashes in March 2022 to 4 crashes in March 2023. 'Failed to yield right of way' doubled in count, from 1 crash to 2 crashes year-over-year, while 'Exceeded authorized speed limit' remained at 1 crash in both periods.

Officer-Reported Primary Contributing Cause

No improper driving14 (48.3%)133.3%prior 6
Inattention4 (13.8%)-42.9%prior 7
Failed to yield right of way2 (6.9%)
Exceeded authorized speed limit1 (3.4%)
Fatigued/asleep1 (3.4%)
Made an improper turn1 (3.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.4%)
Other improper action1 (3.4%)
Disregarded traffic signs, signals, road markings1 (3.4%)
Driving too fast for conditions1 (3.4%)

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

Clear weather remained the most frequent condition for crashes, increasing from 14 crashes in March 2022 to 22 crashes in March 2023. Snow-related weather conditions, including 'Snow' (6 crashes) and 'Snow/Severe crosswinds' (1 crash), were present in March 2023 but absent in March 2022. Correspondingly, road surface conditions showed 'Snow' accounting for 5 crashes in March 2023, while 'Ice' decreased from 2 crashes in March 2022 to 1 crash in March 2023.

Weather

Clear22 (75.9%)
57.1%prior 14
Snow6 (20.7%)
Snow/Severe crosswinds1 (3.4%)

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

Lighting

Daylight14 (48.3%)
16.7%prior 12
Dark - lighted roadway5 (17.2%)
-28.6%prior 7
Dark - roadway not lighted4 (13.8%)
Dawn3 (10.3%)
Dark - unknown roadway lighting2 (6.9%)
Dusk1 (3.4%)

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

Road Surface

Dry19 (65.5%)
58.3%prior 12
Snow5 (17.2%)
Wet4 (13.8%)
-42.9%prior 7
Ice1 (3.4%)

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

Vehicles & Demographics

Top Vehicle Makes (47 vehicles)

1
TOYOTA13 (27.7%)
44.4%prior 9
2
HONDA5 (10.6%)
3
NISSAN3 (6.4%)
4
DODGE3 (6.4%)
5
CHEVROLET2 (4.3%)
6
VOLKSWAGEN2 (4.3%)
7
JEEP2 (4.3%)
8
GMC2 (4.3%)
9
FORD2 (4.3%)
10
SUBARU2 (4.3%)

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

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

Sex Distribution (49 persons with recorded sex)

Female27 (55.1%)
22.7%prior 22
Male22 (44.9%)
29.4%prior 17

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 the 35 mph speed zone saw a substantial increase, rising from 3 crashes in March 2022 to 13 crashes in March 2023. Crashes in the 10 mph zone decreased from 3 crashes to 1 crash year-over-year, while the 55 mph zone maintained 3 crashes in both periods. There were no fatalities reported in any speed zone for either March 2022 or March 2023.

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: TYNGSBOROUGH, MA
  • Total crash records analyzed: 29
  • Total persons involved: 55
  • Total vehicles involved: 47

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). "TYNGSBOROUGH, 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/tyngsborough/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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Tyngsborough, MA Crash Report — March 2023 | ThatCarHitMe.com