ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · DANVERS, MA · DECEMBER 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/danvers/december-2022-report
Monthly Traffic Safety Analysis
39 CRASHES IN
DANVERS, MA
DECEMBER 2022
Total crashes in Danvers decreased by 23.5% year-over-year, from 51 in December 2021 to 39 in December 2022. Concurrently, total injuries fell by 36.8%, from 19 to 12. The most notable shift was the overall reduction in crash incidents and associated injuries.
39
▼ -23.5%was 51
Total Crash Events
0
Persons Killed
12
▼ -36.8%was 19
Persons Injured
2
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash trends in Danvers showed a significant decrease year-over-year, with total crashes falling from 51 to 39, a 23.5% reduction. Total injuries also declined by 36.8%, moving from 19 to 12. This indicates a downward trend in both crash frequency and injury severity.
2
Hit-and-Run Crashes — December 2022
▼ 0.0% vs prior (2)
The number of hit-and-run crashes remained constant at 2 in both December 2022 and December 2021. However, due to a decrease in total crashes, the hit-and-run rate increased from 3.9% in the prior period to 5.1% in the current period. This indicates an upward trend in the proportion of crashes classified as hit-and-run.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
11
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from primarily Thursday (12 crashes) in the prior period to multiple days—Sunday, Wednesday, Thursday, and Saturday—all recording 7 crashes in the current period. The peak hour for crashes also changed, moving from 2 PM (5 crashes) in December 2021 to 5 PM (8 crashes) in December 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at zero in both December 2022 and December 2021. Total injuries decreased by 36.8%, from 19 in the prior period to 12 in the current period. The current period recorded one serious injury (Severity A) crash, which was not present in the prior period, while minor injury (Severity B) crashes decreased from 13 to 5.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
"No improper driving" decreased from 14 crashes in the prior period to 6 crashes in the current period. "Driving too fast for conditions" increased significantly from 1 crash in the prior period to 5 crashes in the current period, becoming the second most frequent factor. "Followed too closely" decreased from 6 crashes to 1 crash year-over-year, while "Inattention" also saw a decrease from 5 to 3 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in "Clear" weather decreased from 25 in the prior period to 14 in the current period, while crashes in "Snow" conditions increased from 2 to 3. There was a notable shift in lighting conditions, with crashes occurring in "Daylight" decreasing from 33 to 15, and crashes in "Dark - lighted roadway" increasing from 16 to 19. "Dry" road surface crashes decreased from 37 to 21, while crashes on "Snow" surfaces increased from 2 to 6.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
Total vehicles involved in crashes decreased from 90 in the prior period to 71 in the current period. While Toyota remained consistent at 11 vehicles in both periods, Ford and Honda swapped top positions, with Ford and Toyota tied for first in the current period (11 each) and Honda decreasing from 13 to 10. The 26-34 age group saw a decrease in representation from 19 persons in the prior period to 13 in the current period, while the 45-54 age group remained a prominent demographic.
Top Vehicle Makes (71 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Vehicle unit records
3 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (77 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The 30 mph speed zone remained the most common for crashes, increasing slightly from 17 in the prior period to 18 in the current period. Crashes in the 40 mph zone decreased from 8 to 3, and in the 65 mph zone from 6 to 2. Conversely, crashes in the 20 mph zone increased from 0 to 4, indicating a shift towards lower speed zones for some incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 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: 2022-12-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-12-01 through 2022-12-31 (31 days)
- Geographic scope: DANVERS, MA
- Total crash records analyzed: 39
- Total persons involved: 80
- Total vehicles involved: 71
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). "DANVERS, MA Crash Intelligence Report: December 2022." Published June 21, 2026. Reporting period: 2022-12-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/danvers/december-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: 2022-12-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved