Monthly Traffic Safety Analysis

24 CRASHES IN
TYNGSBOROUGH, MA
MAY 2023

All metrics benchmarked againstMay 2022

The city of TYNGSBOROUGH, MA experienced a 9.1% increase in total crashes year-over-year, rising from 22 crashes in May 2022 to 24 crashes in May 2023. While no fatalities were reported in either period, the number of injured persons increased by 50%, from 6 to 9. This suggests a notable shift towards a higher incidence of injury-involved crashes.

24

9.1%was 22

Total Crash Events

0

Persons Killed

9

50.0%was 6

Persons Injured

2

100.0%was 1

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in TYNGSBOROUGH, MA increased by 9.1% year-over-year, from 22 crashes in May 2022 to 24 crashes in May 2023. While total fatalities remained at 0 in both periods, the number of injured persons rose by 50%, from 6 in May 2022 to 9 in May 2023.

2

Hit-and-Run Crashes — May 2023

100.0% vs prior (1)

Hit-and-run crashes increased from 1 in May 2022 to 2 in May 2023. This change resulted in the hit-and-run rate rising from 4.5% of total crashes in May 2022 to 8.3% in May 2023. This indicates an upward trend in the proportion of crashes involving a hit-and-run incident.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

9

Motorists Injured

Prior: 650.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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 May 2022, which had 6 crashes, to Wednesday in May 2023, which recorded 7 crashes. Notably, Wednesday crashes increased from 0 in May 2022 to 7 in May 2023. The peak hour also shifted from 4 p.m. (3 crashes) in May 2022 to 5 p.m. (4 crashes) in May 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

No fatal crashes were recorded in either May 2022 or May 2023. However, the total number of injured persons increased from 6 in May 2022 to 9 in May 2023, representing a 50% rise. Crashes resulting in a serious injury (Severity A) increased from 0 in May 2022 to 1 in May 2023, while the share of crashes with no injury decreased from 81.8% to 79.2%.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4.2%
Minor Injury3minor injury crashes12.5%
0.0%prior 3
Possible Injury1possible injury crashes4.2%
0.0%prior 1
No Injury19no injury crashes79.2%
5.6%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "No improper driving" increased from 7 in May 2022 to 10 in May 2023, while "Inattention"-related crashes decreased from 7 to 5. Crashes linked to "Fatigued/asleep" doubled from 1 to 2 year-over-year. Factors such as "Glare" (1 crash) and "Failed to yield right of way" (1 crash) appeared in May 2023 but were not present in May 2022.

Officer-Reported Primary Contributing Cause

No improper driving10 (41.7%)42.9%prior 7
Inattention5 (20.8%)-28.6%prior 7
Fatigued/asleep2 (8.3%)
Glare1 (4.2%)
Failed to yield right of way1 (4.2%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in "Clear" weather conditions increased from 18 in May 2022 to 22 in May 2023. Conversely, crashes in "Cloudy" conditions decreased from 4 to 1, while "Rain/Cloudy" conditions accounted for 1 crash in May 2023. Crashes during "Daylight" increased from 16 to 19, and those in "Dark - roadway not lighted" conditions rose from 1 to 3.

Weather

Clear22 (91.7%)
22.2%prior 18
Cloudy1 (4.2%)
Rain/Cloudy1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash

Lighting

Daylight19 (79.2%)
18.8%prior 16
Dark - roadway not lighted3 (12.5%)
Dark - lighted roadway2 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field

Road Surface

Dry21 (87.5%)
5.0%prior 20
Wet3 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (44 vehicles)

1
TOYOTA10 (22.7%)
100.0%prior 5
2
HONDA9 (20.5%)
50.0%prior 6
3
FORD5 (11.4%)
4
HYUNDAI2 (4.5%)
5
MITS2 (4.5%)
6
VOLKSWAGEN2 (4.5%)
7
CHEVROLET2 (4.5%)
8
VOLVO1 (2.3%)
9
HINO1 (2.3%)
10
MACK1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records

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

Sex Distribution (46 persons with recorded sex)

Male27 (58.7%)
17.4%prior 23
Female19 (41.3%)
18.8%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 35 mph zones increased from 6 in May 2022 to 8 in May 2023, making it the most frequent speed zone for crashes in the current period. Crashes in 45 mph zones decreased from 5 to 3, and crashes in 55 mph zones decreased from 5 to 2. No fatal crashes were recorded across any speed limit zone in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-05-01 through 2023-05-31 (31 days)
  • Geographic scope: TYNGSBOROUGH, MA
  • Total crash records analyzed: 24
  • Total persons involved: 51
  • Total vehicles involved: 44

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: May 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/tyngsborough/may-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 — May 2023 | ThatCarHitMe.com