Monthly Traffic Safety Analysis

150 CRASHES IN
LYNN, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

In March 2023, the city of LYNN recorded 150 total crashes, a decrease of 5.06% compared to the 158 crashes reported in March 2022. The most notable shift was the occurrence of 1 fatality in March 2023, whereas no fatalities were reported in March 2022.

150

-5.1%was 158

Total Crash Events

1

Persons Killed

47

-11.3%was 53

Persons Injured

37

-11.9%was 42

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 11 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, the total number of crashes decreased by 5.06%, from 158 crashes in March 2022 to 150 crashes in March 2023. However, total fatalities increased from 0 to 1, while total injuries decreased from 53 to 47 year-over-year.

37

Hit-and-Run Crashes — March 2023

-11.9% vs prior (42)

The number of hit-and-run crashes decreased from 42 in March 2022 to 37 in March 2023. Consequently, the hit-and-run rate decreased from 26.6% to 24.7%, indicating a downward trend.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Motorists Killed

Prior: 00.0%

6

Pedestrians Injured

Prior: 7-14.3%

41

Motorists Injured

Prior: 45-8.9%

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 remained Wednesday in both periods, with 31 crashes in March 2023 compared to 29 in March 2022. The peak hour for crashes shifted from 7 AM with 14 crashes in March 2022 to 2 PM with 17 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

The fatal crash rate increased from 0% in March 2022 to 0.7% in March 2023, with 1 fatal crash occurring in the current period. Serious injuries decreased from 4 to 2, while minor injuries increased from 30 to 32 year-over-year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.7%
Serious Injury2serious injury crashes1.3%
-50.0%prior 4
Minor Injury32minor injury crashes21.3%
6.7%prior 30
Possible Injury3possible injury crashes2%
0.0%prior 3
No Injury101no injury crashes67.3%
-3.8%prior 105

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 count of 'No improper driving' as a contributing factor increased from 40 in March 2022 to 61 in March 2023, a 52.5% increase. Conversely, 'Inattention' decreased in count from 8 to 5, representing a 37.5% reduction. 'Other improper action' increased from 3 to 5 incidents, a 66.7% rise in count.

Officer-Reported Primary Contributing Cause

No improper driving61 (40.7%)52.5%prior 40
Inattention5 (3.3%)-37.5%prior 8
Other improper action5 (3.3%)
Disregarded traffic signs, signals, road markings4 (2.7%)
Fatigued/asleep4 (2.7%)
Over-correcting/over-steering3 (2%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (2%)
Made an improper turn3 (2%)
Failed to yield right of way3 (2%)
Distracted2 (1.3%)

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

Crashes occurring in clear weather conditions slightly increased from 110 in March 2022 to 112 in March 2023. Crashes on wet road surfaces decreased from 34 to 28, while crashes in dark-lighted roadway conditions decreased from 54 to 51.

Weather

Clear91 (60.7%)
-8.1%prior 99
Clear/Clear21 (14.0%)
90.9%prior 11
Rain12 (8.0%)
-33.3%prior 18
Cloudy8 (5.3%)
-42.9%prior 14
Snow6 (4.0%)
20.0%prior 5
Sleet, hail (freezing rain or drizzle)3 (2.0%)
Snow/Rain2 (1.3%)
Cloudy/Cloudy2 (1.3%)
Snow/Snow1 (0.7%)
Cloudy/Clear1 (0.7%)

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

Lighting

Daylight86 (57.3%)
-2.3%prior 88
Dark - lighted roadway51 (34.0%)
-5.6%prior 54
Dark - unknown roadway lighting5 (3.3%)
Dawn5 (3.3%)
-16.7%prior 6
Dusk2 (1.3%)
Dark - roadway not lighted1 (0.7%)

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

Road Surface

Dry116 (77.3%)
-0.9%prior 117
Wet28 (18.7%)
-17.6%prior 34
Snow3 (2.0%)
Slush2 (1.3%)
Ice1 (0.7%)

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 persons involved in crashes decreased from 429 in March 2022 to 372 in March 2023. There was a notable increase in persons aged 16-20, from 28 to 42, and in persons aged 55-64, from 25 to 31. The top vehicle makes involved, Honda, Toyota, and Ford, all saw a decrease in their counts year-over-year.

Top Vehicle Makes (290 vehicles)

1
HONDA67 (23.1%)
-8.2%prior 73
2
TOYOTA53 (18.3%)
-1.9%prior 54
3
FORD32 (11%)
-27.3%prior 44
4
CHEVROLET19 (6.6%)
5.6%prior 18
5
NISSAN19 (6.6%)
18.8%prior 16
6
JEEP18 (6.2%)
12.5%prior 16
7
ACURA9 (3.1%)
80.0%prior 5
8
GMC9 (3.1%)
28.6%prior 7
9
HYUNDAI8 (2.8%)
0.0%prior 8
10
BMW5 (1.7%)
-16.7%prior 6

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

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

Sex Distribution (311 persons with recorded sex)

Male190 (61.1%)
-6.4%prior 203
Female121 (38.9%)
-18.8%prior 149

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 25 mph zones decreased from 90 in March 2022 to 77 in March 2023, and in 30 mph zones from 45 to 43. A fatal crash occurred in a 30 mph zone in March 2023, resulting in a 2.326% fatal rate for that zone, whereas no fatal crashes were recorded in any speed zone in March 2022.

Fatal crashes by zone: 30 mph: 1 of 43 (2.326%)

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: LYNN, MA
  • Total crash records analyzed: 150
  • Total persons involved: 372
  • Total vehicles involved: 290

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). "LYNN, 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/lynn/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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Lynn, MA Crash Report — March 2023 | ThatCarHitMe.com