Monthly Traffic Safety Analysis

55 CRASHES IN
WOBURN, MA
FEBRUARY 2023

All metrics benchmarked againstFebruary 2022

Total crashes in WOBURN decreased by 36.8% year-over-year, falling from 87 in February 2022 to 55 in February 2023. This period also saw a significant positive shift in safety, with total fatalities decreasing from 2 to 0.

55

▼ -36.8%was 87

Total Crash Events

0

▼ -100.0%was 2

Persons Killed

13

▼ -48.0%was 25

Persons Injured

5

▲ 25.0%was 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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a decrease in crash activity, with total crashes falling from 87 in February 2022 to 55 in February 2023, representing a 36.8% reduction. Total fatalities also decreased from 2 to 0 year-over-year.

5

Hit-and-Run Crashes — February 2023

▲ 25.0% vs prior (4)

The number of hit-and-run crashes increased from 4 in February 2022 to 5 in February 2023. The hit-and-run crash rate also increased from 4.6% of total crashes in February 2022 to 9.1% in February 2023.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1↓-100.0%

13

Motorists Injured

Prior: 25↓-48.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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 Friday, which had 17 crashes in February 2022, to Sunday, with 9 crashes in February 2023. The peak crash hour also shifted from 7p, with 10 crashes in February 2022, to 3p, with 7 crashes in February 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total fatalities decreased from 2 in February 2022 to 0 in February 2023. The proportion of minor injury crashes remained stable at 12.6% in February 2022 and 12.7% in February 2023, while possible injury crashes decreased from a 5.7% share to a 3.6% share.

Outcome by Severity (Crash Events)

Minor Injury7minor injury crashes12.7%
↓-36.4%prior 11
Possible Injury2possible injury crashes3.6%
↓-60.0%prior 5
No Injury45no injury crashes81.8%
↓-32.8%prior 67

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Most severe injury per crash record

Top Contributing Factors

The count of crashes attributed to 'No improper driving' decreased from 23 in February 2022 to 19 in February 2023. Crashes due to 'Followed too closely' saw a notable decrease in count, falling from 13 to 6 year-over-year. Conversely, crashes where 'Failed to yield right of way' was a factor increased in count from 3 to 5.

Officer-Reported Primary Contributing Cause

No improper driving19 (34.5%)↓-17.4%prior 23
Inattention9 (16.4%)↓-25.0%prior 12
Followed too closely6 (10.9%)↓-53.8%prior 13
Failed to yield right of way5 (9.1%)
Distracted2 (3.6%)
Failure to keep in proper lane or running off road2 (3.6%)
Made an improper turn1 (1.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (1.8%)
Over-correcting/over-steering1 (1.8%)
Physical impairment1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather decreased from 52 in February 2022 to 36 in February 2023. There was a significant reduction in crashes on 'Wet' road surfaces, falling from 23 in February 2022 to 4 in February 2023. Crashes during 'Daylight' conditions decreased from 47 to 29 year-over-year.

Weather

Clear36 (67.9%)
↓-30.8%prior 52
Cloudy4 (7.5%)
↓-50.0%prior 8
Snow4 (7.5%)
↓-42.9%prior 7
Clear/Other2 (3.8%)
Cloudy/Snow2 (3.8%)
Snow/Blowing sand, snow2 (3.8%)
Clear/Cloudy1 (1.9%)
Snow/Sleet, hail (freezing rain or drizzle)1 (1.9%)
Sleet, hail (freezing rain or drizzle)1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Weather condition at time of crash

Lighting

Daylight29 (53.7%)
↓-38.3%prior 47
Dark - lighted roadway20 (37.0%)
↓-28.6%prior 28
Dark - roadway not lighted3 (5.6%)
Dawn1 (1.9%)
Dusk1 (1.9%)
↓-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Lighting condition field

Road Surface

Dry42 (76.4%)
↓-6.7%prior 45
Snow6 (10.9%)
↓-45.5%prior 11
Wet4 (7.3%)
↓-82.6%prior 23
Ice2 (3.6%)
↓-71.4%prior 7
Slush1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 170 in February 2022 to 112 in February 2023. The 26-34 age group saw the largest decrease in persons involved, falling from 41 to 21 persons year-over-year. While Toyota remained the top vehicle make involved, its count decreased from 33 to 25, and Honda's involvement decreased from 28 to 13.

Top Vehicle Makes (112 vehicles)

1
TOYOTA25 (22.3%)
↓-24.2%prior 33
2
HONDA13 (11.6%)
↓-53.6%prior 28
3
FORD7 (6.3%)
↓-36.4%prior 11
4
JEEP6 (5.4%)
↓-25.0%prior 8
5
NISSAN6 (5.4%)
↓-53.8%prior 13
6
SUBARU6 (5.4%)
7
VOLKSWAGEN5 (4.5%)
→0.0%prior 5
8
KIA4 (3.6%)
9
AUDI3 (2.7%)
10
BMW3 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Vehicle unit records

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

Sex Distribution (110 persons with recorded sex)

Male67 (60.9%)
↓-28.7%prior 94
Female43 (39.1%)
↓-46.3%prior 80

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph speed zones saw a significant decrease, falling from 37 in February 2022 to 19 in February 2023, with fatalities in this zone decreasing from 2 to 0. Crashes in 55 mph zones also decreased from 15 to 7. Conversely, crashes in 20 mph zones increased from 4 to 5, and in 25 mph zones from 3 to 5.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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: 2023-02-01 through 2023-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-02-01 through 2023-02-28 (28 days)
  • Geographic scope: WOBURN, MA
  • Total crash records analyzed: 55
  • Total persons involved: 122
  • Total vehicles involved: 112

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). "WOBURN, MA Crash Intelligence Report: February 2023." Published June 21, 2026. Reporting period: 2023-02-01 to 2023-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/woburn/february-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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Woburn, MA Crash Report — February 2023 | ThatCarHitMe.com