ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LYNNFIELD, MA · 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/lynnfield/2022-annual-report
Yearly Traffic Safety Analysis
295 CRASHES IN
LYNNFIELD, MA
2022
In 2022, Lynnfield recorded 295 total crashes, a 5.0% increase from the 281 crashes documented in 2021. The total number of injuries rose from 76 to 85, an 11.8% increase year-over-year. The most significant change was the occurrence of one fatal crash in 2022, resulting in one fatality, whereas no fatal crashes were recorded in the prior year.
295
▲ 5.0%was 281
Total Crash Events
1
Persons Killed
85
▲ 11.8%was 76
Persons Injured
11
▲ 57.1%was 7
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic collisions in Lynnfield trended upward in 2022 compared to the previous year. The total number of crashes increased by 5.0%, rising from 281 to 295. This was accompanied by an 11.8% increase in the number of people injured, which grew from 76 in 2021 to 85 in 2022, and one fatality recorded in 2022 compared to none in 2021.
11
Hit-and-Run Crashes — 2022
▲ 57.1% vs prior (7)
Hit-and-run incidents increased in both count and rate in 2022 compared to the prior year. The number of hit-and-run crashes rose by 57.1%, from 7 incidents in 2021 to 11 in 2022. As a proportion of all collisions, the hit-and-run rate increased from 2.5% in 2021 to 3.7% in 2022.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
2
Pedestrians Injured
2
Cyclists Injured
81
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed both consistency and change year-over-year. Friday remained the peak day for crashes in both 2022 (54 crashes) and 2021 (57 crashes). However, the peak hour for collisions shifted from 2 p.m. in 2021 (23 crashes) to 6 p.m. in 2022 (27 crashes). Additionally, crashes occurring on Sunday saw a significant increase, rising from 30 incidents in 2021 to 48 in 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity worsened in 2022, marked by the city's first fatal crash in this two-year period, which resulted in one fatality. The number of crashes involving serious injuries also doubled, increasing from 3 in 2021 to 6 in 2022. While crashes involving minor injuries decreased from 48 to 41, the number of crashes with no reported injuries grew from 206 to 228, making up 77.3% of all incidents in 2022 compared to 73.3% in 2021.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The top three contributing factors to crashes remained consistent across both years: 'No improper driving', 'Followed too closely', and 'Inattention'. However, the count for crashes attributed to 'Followed too closely' increased by 21.1%, from 38 to 46 incidents. In contrast, crashes linked to 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased in count by 55.6% (from 9 to 4), and those involving a 'Fatigued/asleep' driver fell by 75% (from 8 to 2).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
While the distribution of crashes by weather condition remained stable, there was a notable shift in road surface conditions. The number of crashes on adverse road surfaces like wet, snow, or ice increased by 44%, from 50 incidents in 2021 to 72 in 2022. Consequently, the share of crashes on these surfaces grew from 17.8% to 24.4% of all collisions. In terms of lighting, crashes in daylight conditions increased from 190 to 212, while crashes in dark conditions decreased from 80 to 74.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes were Toyota, Ford, and Honda in both years, though their order changed. Toyota's involvement increased significantly from 66 vehicles in 2021 to 98 in 2022, making it the most common make. An analysis of persons involved shows a shift in age demographics, with the 26-34 age group's involvement increasing from 95 to 133 individuals, while the 21-25 age group's involvement decreased from 80 to 59. The number of children aged 0-15 involved in crashes more than doubled, from 16 to 36.
Top Vehicle Makes (558 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
28 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (628 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
In 2022, there was a shift in where crashes occurred relative to posted speed limits. The proportion of crashes in lower-speed zones (35 mph or less) increased, accounting for 58.0% of incidents with speed data, up from 52.8% in 2021. Conversely, the share of crashes in higher-speed zones (50 mph or more) decreased from 47.2% to 42.0%. The single fatal crash recorded in 2022 occurred in a 25 mph zone.
Fatal crashes by zone: 25 mph: 1 of 41 (2.439%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: LYNNFIELD, MA
- Total crash records analyzed: 295
- Total persons involved: 690
- Total vehicles involved: 558
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). "LYNNFIELD, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lynnfield/2022-annual-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: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved