ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · LYNN, MA · MARCH 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/lynn/march-2022-report
Monthly Traffic Safety Analysis
158 CRASHES IN
LYNN, MA
MARCH 2022
In March 2022, the city of LYNN experienced 158 crashes, a substantial increase compared to 105 crashes in March 2021. This represents a 50.48% rise in total crashes year-over-year. A particularly notable shift was the doubling of hit-and-run crashes, which rose from 21 incidents in the prior period to 42 in the current period.
158
▲ 50.5%was 105
Total Crash Events
0
Persons Killed
53
▲ 89.3%was 28
Persons Injured
42
▲ 100.0%was 21
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. 16 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash data for March in LYNN indicates an upward trend year-over-year, with total crashes increasing by 53 incidents. Total injuries also saw a significant rise, from 28 in March 2021 to 53 in March 2022. There were no reported fatalities in either period, maintaining stability at zero.
42
Hit-and-Run Crashes — March 2022
▲ 100.0% vs prior (21)
Hit-and-run crashes in LYNN doubled year-over-year, increasing from 21 incidents in March 2021 to 42 incidents in March 2022. This led to an upward trend in the hit-and-run rate, which rose from 20% of all crashes in the prior period to 26.6% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
0
Other Killed
7
Pedestrians Injured
45
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Temporal patterns for crashes shifted between the two periods. The peak day for crashes moved from Tuesday with 26 incidents in March 2021 to Wednesday with 29 incidents in March 2022. Similarly, the peak hour for crashes changed from 11 AM with 11 incidents in the prior year to 7 AM with 14 incidents in the current year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at zero in both March 2021 and March 2022. However, total injuries increased from 28 to 53 year-over-year. Serious injuries (Severity A) saw an increase from 1 crash (1% of total) to 4 crashes (2.5% of total), while minor injuries (Severity B) rose from 17 crashes (16.2%) to 30 crashes (19%).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw changes in crash counts year-over-year. 'No improper driving' increased from 26 crashes in March 2021 to 40 crashes in March 2022. Crashes attributed to 'Inattention' quadrupled from 2 to 8, and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' doubled from 2 to 4 incidents. Conversely, 'Other improper action' decreased from 5 crashes to 3 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Adverse weather and road conditions contributed to more crashes in March 2022 compared to the prior year. Crashes occurring during 'Rain' increased from 0 to 18, and 'Snow' conditions from 0 to 5. The number of crashes on 'Wet' road surfaces rose significantly from 1 in March 2021 to 34 in March 2022.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Road surface condition field
Vehicles & Demographics
Honda and Toyota remained the top two vehicle makes involved in crashes, though their rankings shifted with Honda now leading at 73 crashes (up from 45) and Toyota at 54 crashes (up from 45). There was a notable increase in persons involved in crashes across most age groups, particularly for the 21-25 age group (from 22 to 52) and the 35-44 age group (from 38 to 63).
Top Vehicle Makes (311 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Vehicle unit records
92 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (352 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph speed zones increased substantially from 47 incidents in March 2021 to 90 incidents in March 2022. Crashes in 30 mph zones also rose from 39 to 45 over the same period. No fatalities were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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: 2022-03-01 through 2022-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-03-01 through 2022-03-31 (31 days)
- Geographic scope: LYNN, MA
- Total crash records analyzed: 158
- Total persons involved: 429
- Total vehicles involved: 311
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 2022." Published June 21, 2026. Reporting period: 2022-03-01 to 2022-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lynn/march-2022-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-03-01 – 2022-03-31
Generated: June 21, 2026 · All rights reserved