Monthly Traffic Safety Analysis

164 CRASHES IN
LYNN, MA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

In September 2024, Lynn experienced 164 crashes, a decrease of 6 crashes or 3.53% compared to the 170 crashes reported in September 2023. The most significant year-over-year change was the increase in total fatalities from 0 in the prior period to 1 in the current period.

164

-3.5%was 170

Total Crash Events

1

Persons Killed

58

-9.4%was 64

Persons Injured

37

23.3%was 30

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Lynn showed a slight downward trend year-over-year, with total crashes decreasing by 6, representing a 3.53% reduction. However, this period saw an increase in fatalities, rising from 0 in September 2023 to 1 in September 2024, while total injuries decreased by 6, a 9.38% reduction.

37

Hit-and-Run Crashes — September 2024

23.3% vs prior (30)

Hit-and-run incidents increased year-over-year, with 37 crashes reported in September 2024 compared to 30 in September 2023, an increase of 7 crashes. The hit-and-run rate also rose by 5 percentage points, from 17.6% of all crashes in the prior period to 22.6% in the current period, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

8

Pedestrians Injured

Prior: 714.3%

3

Cyclists Injured

Prior: 30.0%

44

Motorists Injured

Prior: 52-15.4%

3

Other Injured

Prior: 250.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal patterns for crashes remained consistent year-over-year, with Sunday continuing to be the peak day for crashes in both September 2023 and September 2024. The peak hour for crashes also remained at 4 PM in both periods. Sunday crashes decreased slightly from 29 to 28, and crashes at 4 PM decreased from 17 to 14.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution shifted notably, with a fatal crash occurring in September 2024, resulting in 1 fatality, compared to zero fatal crashes and fatalities in September 2023. Total injuries decreased from 64 to 58 year-over-year. The prior period reported 6 serious injuries, a category not present in the current period, while minor injuries increased from 34 to 39.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
Minor Injury39minor injury crashes23.8%
14.7%prior 34
Possible Injury6possible injury crashes3.7%
-14.3%prior 7
No Injury106no injury crashes64.6%
-7.0%prior 114

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'No improper driving', remained consistent with 62 crashes in both September 2023 and September 2024. 'Other improper action' crashes increased by 1, from 10 to 11, while 'Inattention' decreased by 3 crashes, from 10 to 7. Crashes attributed to 'Fatigued/asleep' drivers increased by 3, from 1 to 4 crashes.

Officer-Reported Primary Contributing Cause

No improper driving62 (37.8%)0.0%prior 62
Other improper action11 (6.7%)10.0%prior 10
Inattention7 (4.3%)-30.0%prior 10
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner7 (4.3%)-12.5%prior 8
Distracted4 (2.4%)-20.0%prior 5
Fatigued/asleep4 (2.4%)
Made an improper turn3 (1.8%)
Failed to yield right of way3 (1.8%)
Failure to keep in proper lane or running off road3 (1.8%)
Disregarded traffic signs, signals, road markings2 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased by 9, from 126 in September 2023 to 135 in September 2024, while crashes in rainy conditions decreased by 12, from 28 to 16. There was a notable shift in lighting conditions, with daylight crashes decreasing by 17 (from 120 to 103) and crashes in dark-lighted roadways increasing by 10 (from 43 to 53). Crashes on dry road surfaces increased by 15 (from 131 to 146), whereas crashes on wet surfaces decreased by 21 (from 39 to 18).

Weather

Clear115 (70.1%)
10.6%prior 104
Clear/Clear20 (12.2%)
-9.1%prior 22
Cloudy12 (7.3%)
-14.3%prior 14
Rain9 (5.5%)
-57.1%prior 21
Cloudy/Rain4 (2.4%)
Rain/Cloudy2 (1.2%)
Rain/Rain1 (0.6%)
-83.3%prior 6
Sleet, hail (freezing rain or drizzle)/Sleet, hail (freezing rain or drizzle)1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash

Lighting

Daylight103 (62.8%)
-14.2%prior 120
Dark - lighted roadway53 (32.3%)
23.3%prior 43
Dusk3 (1.8%)
Dark - roadway not lighted2 (1.2%)
Dark - unknown roadway lighting2 (1.2%)
Dawn1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field

Road Surface

Dry146 (89.0%)
11.5%prior 131
Wet18 (11.0%)
-53.8%prior 39

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 328 to 314 year-over-year. While Honda remained the top vehicle make involved, its count decreased by 4 (from 70 to 66), and Ford saw a decrease of 11 vehicles (from 37 to 26). In terms of person demographics, there was a significant decrease of 39 persons in the 0-15 age group involved in crashes (from 64 to 25), while the 26-34 and 35-44 age groups saw increases of 15 and 13 persons respectively.

Top Vehicle Makes (314 vehicles)

1
HONDA66 (21%)
-5.7%prior 70
2
TOYOTA62 (19.7%)
12.7%prior 55
3
FORD26 (8.3%)
-29.7%prior 37
4
CHEVROLET24 (7.6%)
26.3%prior 19
5
NISSAN21 (6.7%)
-12.5%prior 24
6
SUBARU12 (3.8%)
140.0%prior 5
7
KIA11 (3.5%)
37.5%prior 8
8
JEEP10 (3.2%)
0.0%prior 10
9
GMC9 (2.9%)
10
DODGE6 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records

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

Sex Distribution (356 persons with recorded sex)

Male222 (62.4%)
-4.7%prior 233
Female134 (37.6%)
-29.1%prior 189

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones saw minor shifts, with crashes in the 25 mph zone increasing by 7, from 87 to 94. Conversely, crashes in the 30 mph zone decreased by 6, from 36 to 30. Notably, the single fatality in September 2024 occurred within a 30 mph speed zone, whereas no fatalities were recorded in any speed zone in September 2023.

Fatal crashes by zone: 30 mph: 1 of 30 (3.333%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-09-01 through 2024-09-30 (30 days)
  • Geographic scope: LYNN, MA
  • Total crash records analyzed: 164
  • Total persons involved: 430
  • Total vehicles involved: 314

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: September 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lynn/september-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 — September 2024 | ThatCarHitMe.com