ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LYNN, MA · 2023
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/2023-annual-report
Yearly Traffic Safety Analysis
2,043 CRASHES IN
LYNN, MA
2023
In 2023, Lynn recorded 2,043 total traffic crashes, a 2.6% decrease from the 2,098 crashes reported in 2022. While overall crashes declined, the number of crashes involving a driver under the influence of alcohol increased by 41.4%, rising from 58 incidents in 2022 to 82 in 2023. Total fatalities remained stable at 3 for both years.
2,043
▼ -2.6%was 2,098
Total Crash Events
3
Persons Killed
757
▲ 1.2%was 748
Persons Injured
458
▼ -4.8%was 481
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 152 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in traffic crashes in Lynn shows a slight decrease year-over-year, with total incidents falling by 2.6% from 2,098 in 2022 to 2,043 in 2023. Despite the drop in total crashes, the number of reported injuries increased by 1.2% from 748 to 757. The number of total fatalities remained unchanged at 3 for both periods.
458
Hit-and-Run Crashes — 2023
▼ -4.8% vs prior (481)
The number of hit-and-run incidents saw a slight decrease year-over-year. The total count of hit-and-run crashes fell from 481 in 2022 to 458 in 2023. Correspondingly, the hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, also decreased marginally from 22.9% in 2022 to 22.4% in 2023.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
0
Other Killed
86
Pedestrians Injured
21
Cyclists Injured
644
Motorists Injured
6
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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 some shifts between the two periods. The peak day for crashes moved from Saturday (351 crashes) in 2022 to Sunday (327 crashes) in 2023. The peak hour for collisions, however, remained consistent at 2 PM in both years, with crash counts of 143 in 2022 and 155 in 2023 during that hour.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes remained relatively stable year-over-year, with the number of fatal crashes holding steady at 3 for both 2022 and 2023. The fatal crash rate saw a minor increase from 0.14 to 0.15 per 100 crashes, reflecting the slight drop in total incidents. The proportion of crashes resulting in any level of injury (serious, minor, or possible) increased slightly from 27.4% of all crashes in 2022 to 28.5% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'No improper driving' remained the most cited factor in both years, its count increased from 622 in 2022 to 730 in 2023. Several key improper driving factors saw significant year-over-year increases in their reported counts. Crashes attributed to 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' rose by 56.7% from 60 to 94 incidents, and those linked to 'Other improper action' increased by 84.8% from 46 to 85 incidents. Similarly, crashes involving 'Inattention' grew from 69 to 85 incidents, a 23.2% increase in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in both years predominantly occurred in clear weather and on dry roads. However, the proportion of crashes in non-clear weather conditions (including rain, clouds, and snow) increased from 21.2% of crashes in 2022 to 26.0% in 2023. Correspondingly, the number of crashes on wet road surfaces rose from 298 to 379. The distribution of crashes by lighting conditions remained nearly unchanged, with daylight crashes accounting for approximately 58% of all incidents in both years.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The types of vehicles involved in crashes remained consistent, with Honda, Toyota, and Ford being the top three most common makes in both 2022 and 2023, with very similar counts. The age demographics of persons involved also showed a similar pattern, with the 26-34 age group representing the largest cohort in both years. However, the number of individuals from this group involved in crashes decreased from 963 in 2022 to 882 in 2023.
Top Vehicle Makes (3,989 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
1,193 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (4,520 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
The majority of crashes in both periods occurred in zones with posted speed limits of 25 mph and 30 mph. In 2023, these two zones accounted for 1,622 crashes, down from 1,724 in 2022. Fatal crashes were distributed across different speed zones; in 2023, one fatality occurred in each of the 25, 30, and 35 mph zones. This differs from 2022, which recorded one fatality in each of the 15, 25, and 30 mph zones.
Fatal crashes by zone: 25 mph: 1 of 1,169 (0.086%) · 30 mph: 1 of 453 (0.221%) · 35 mph: 1 of 130 (0.769%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: LYNN, MA
- Total crash records analyzed: 2,043
- Total persons involved: 5,580
- Total vehicles involved: 3,989
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lynn/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved