ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SALEM, MA · FEBRUARY 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/salem/february-2022-report
Monthly Traffic Safety Analysis
61 CRASHES IN
SALEM, MA
FEBRUARY 2022
In February 2022, Salem experienced 61 crashes, an increase from the 51 crashes reported in February 2021. This represents a 19.6% rise in total crash incidents year-over-year. A significant change was observed in total injuries, which more than doubled from 7 in the prior period to 15 in the current period, marking a 114.3% increase.
61
▲ 19.6%was 51
Total Crash Events
0
Persons Killed
15
▲ 114.3%was 7
Persons Injured
7
▲ 75.0%was 4
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 · 2022-02-01 to 2022-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in Salem are trending upwards year-over-year, with a 19.6% increase from 51 crashes in February 2021 to 61 crashes in February 2022. This rise was accompanied by a substantial 114.3% increase in total injuries, climbing from 7 to 15 during the same period.
7
Hit-and-Run Crashes — February 2022
▲ 75.0% vs prior (4)
Hit-and-run incidents increased from 4 crashes in February 2021 to 7 crashes in February 2022. This rise also translated to an increase in the hit-and-run rate, which climbed from 7.8% of total crashes in the prior period to 11.5% in the current period, indicating an upward trend.
Vulnerable Road User Casualties
0
Motorists Killed
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · 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 Saturday, with 12 crashes in February 2021, to Tuesday, with 13 crashes in February 2022. Similarly, the peak hour for crashes moved from 3 p.m. (5 crashes) in the prior year to 5 p.m. (6 crashes) in the current year. Crashes on weekdays, particularly Monday (2 to 12) and Tuesday (9 to 13), saw notable increases, while Saturday crashes decreased from 12 to 7.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both February 2021 and February 2022. However, injury crashes collectively increased from 6 (11.7% of total crashes) in the prior period to 10 (16.4% of total crashes) in the current period. Specifically, minor injury crashes more than doubled from 2 to 5, while possible injury crashes increased from 4 to 5.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Most severe injury per crash record
Top Contributing Factors
The number of crashes attributed to 'No improper driving' decreased from 9 in February 2021 to 5 in February 2022. Conversely, 'Failed to yield right of way' crashes increased from 3 to 5, and crashes involving 'Disregarded traffic signs, signals, road markings' rose from 1 to 3. 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway' emerged as a factor in 4 crashes in the current period, having not been present in the prior period's listed factors.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear/Clear' weather conditions significantly increased from 23 to 44, while 'Snow/Snow' conditions saw a decrease from 11 to 4 crashes. Correspondingly, crashes on 'Dry' road surfaces nearly doubled from 20 to 39, while those on 'Snow' surfaces dropped from 10 to 3. Crashes in 'Daylight' conditions rose from 31 to 35, and those in 'Dark - lighted roadway' conditions increased from 16 to 23.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased from 113 to 142 year-over-year. The 26-34 age group saw a notable increase in representation, from 23 persons in the prior period to 31 in the current period, as did the 35-44 age group, from 16 to 22 persons. Among vehicle makes, Honda crashes increased from 20 to 28, while Toyota crashes slightly decreased from 16 to 14, and Ford crashes rose from 8 to 13.
Top Vehicle Makes (113 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (128 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Person-level records linked to crash events
Speed Limit Zones
The total number of crashes with a recorded speed limit increased from 27 in February 2021 to 35 in February 2022. Crashes occurring in 25 mph zones increased from 15 to 18, and those in 30 mph zones rose from 7 to 9. Fatal crashes remained at zero across all speed limit categories in both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · 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: 2022-02-01 through 2022-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-02-01 through 2022-02-28 (28 days)
- Geographic scope: SALEM, MA
- Total crash records analyzed: 61
- Total persons involved: 142
- Total vehicles involved: 113
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). "SALEM, MA Crash Intelligence Report: February 2022." Published June 21, 2026. Reporting period: 2022-02-01 to 2022-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/salem/february-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: 2022-02-01 – 2022-02-28
Generated: June 21, 2026 · All rights reserved