Monthly Traffic Safety Analysis

173 CRASHES IN
LYNN, MA
JUNE 2024

All metrics benchmarked againstJune 2023

Total crashes in LYNN, MA for June 2024 were 173, a slight decrease from 175 crashes in June 2023. Fatalities remained constant at 1 in both periods. The most notable shift was a 20% reduction in total injuries, decreasing from 70 in June 2023 to 56 in June 2024.

173

-1.1%was 175

Total Crash Events

1

Persons Killed

56

-20.0%was 70

Persons Injured

45

32.4%was 34

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in crashes for June shows a stable pattern with a minor decline, decreasing from 175 crashes in June 2023 to 173 crashes in June 2024. This represents a 1.14% reduction year-over-year.

45

Hit-and-Run Crashes — June 2024

32.4% vs prior (34)

Hit-and-run crashes increased from 34 in June 2023 to 45 in June 2024, an increase of 11 crashes. The hit-and-run rate also rose from 19.4% of total crashes in June 2023 to 26% in June 2024, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 10.0%

0

Other Killed

Prior: 00.0%

5

Pedestrians Injured

Prior: 50.0%

2

Cyclists Injured

Prior: 3-33.3%

48

Motorists Injured

Prior: 62-22.6%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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 Saturday in both periods, with crashes on Saturdays increasing from 30 in June 2023 to 37 in June 2024. The peak hour for crashes shifted from 6p in June 2023 to 12p in June 2024, with both hours recording 15 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes remained constant at 1 in both June 2023 and June 2024. Serious injury crashes increased from 2 to 3, while possible injury crashes decreased from 12 to 6. Overall, total injuries saw a 20% reduction, decreasing from 70 to 56.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
0.0%prior 1
Serious Injury3serious injury crashes1.7%
50.0%prior 2
Minor Injury38minor injury crashes22%
2.7%prior 37
Possible Injury6possible injury crashes3.5%
-50.0%prior 12
No Injury103no injury crashes59.5%
-7.2%prior 111

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' saw a notable increase, rising from 4 crashes in June 2023 to 11 crashes in June 2024. Conversely, 'No improper driving' decreased from 62 crashes to 58 crashes. 'Inattention' remained constant at 9 crashes in both periods.

Officer-Reported Primary Contributing Cause

No improper driving58 (33.5%)-6.5%prior 62
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner11 (6.4%)
Inattention9 (5.2%)0.0%prior 9
Failed to yield right of way5 (2.9%)0.0%prior 5
Other improper action5 (2.9%)-28.6%prior 7
Failure to keep in proper lane or running off road4 (2.3%)
Physical impairment4 (2.3%)
Over-correcting/over-steering4 (2.3%)
Followed too closely2 (1.2%)
Made an improper turn2 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a shift towards crashes occurring in clear weather and on dry roads in June 2024 compared to June 2023. Crashes in clear conditions (Clear and Clear/Clear) increased from 113 to 139, while crashes in rainy conditions decreased from 29 to 17. Similarly, crashes on wet roads decreased from 38 to 24.

Weather

Clear126 (74.1%)
31.3%prior 96
Clear/Clear13 (7.6%)
-23.5%prior 17
Rain13 (7.6%)
-45.8%prior 24
Cloudy8 (4.7%)
-50.0%prior 16
Cloudy/Rain2 (1.2%)
Cloudy/Cloudy2 (1.2%)
Rain/Cloudy2 (1.2%)
Rain/Rain2 (1.2%)
Sleet, hail (freezing rain or drizzle)1 (0.6%)
Unknown/Unknown1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Weather condition at time of crash

Lighting

Daylight114 (67.1%)
-5.8%prior 121
Dark - lighted roadway45 (26.5%)
12.5%prior 40
Dusk5 (2.9%)
0.0%prior 5
Dark - unknown roadway lighting3 (1.8%)
Dark - roadway not lighted2 (1.2%)
Dawn1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Lighting condition field

Road Surface

Dry146 (85.4%)
7.4%prior 136
Wet24 (14.0%)
-36.8%prior 38
Sand, mud, dirt, oil, gravel1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes slightly increased from 346 to 351 year-over-year. Honda remained the top vehicle make, increasing from 65 to 73 vehicles, while Toyota moved to second place with 50 vehicles, and Ford dropped to third with 39 vehicles. Crashes involving persons aged 21-25 increased from 48 to 57, while those aged 26-34 decreased from 89 to 75.

Top Vehicle Makes (351 vehicles)

1
HONDA73 (20.8%)
12.3%prior 65
2
TOYOTA50 (14.2%)
-2.0%prior 51
3
FORD39 (11.1%)
-26.4%prior 53
4
CHEVROLET30 (8.5%)
11.1%prior 27
5
NISSAN27 (7.7%)
22.7%prior 22
6
ACURA12 (3.4%)
33.3%prior 9
7
HYUNDAI10 (2.8%)
25.0%prior 8
8
DODGE8 (2.3%)
9
JEEP7 (2%)
-69.6%prior 23
10
MAZDA7 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Vehicle unit records

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

Sex Distribution (354 persons with recorded sex)

Male216 (61.0%)
-8.1%prior 235
Female138 (39.0%)
-10.4%prior 154

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Person-level records linked to crash events

Speed Limit Zones

The majority of crashes in both periods occurred in 25 mph zones, with a slight increase from 97 crashes in June 2023 to 99 crashes in June 2024. Crashes in 30 mph zones increased from 33 to 36, and this zone recorded the single fatal crash in June 2024. Conversely, crashes in 35 mph zones decreased from 15 to 11, and this zone did not record any fatal crashes in June 2024, unlike the prior year.

Fatal crashes by zone: 30 mph: 1 of 36 (2.778%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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: 2024-06-01 through 2024-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-06-01 through 2024-06-30 (30 days)
  • Geographic scope: LYNN, MA
  • Total crash records analyzed: 173
  • Total persons involved: 453
  • Total vehicles involved: 351

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: June 2024." Published June 21, 2026. Reporting period: 2024-06-01 to 2024-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lynn/june-2024-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 — June 2024 | ThatCarHitMe.com