ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SALEM, 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/salem/2022-annual-report
Yearly Traffic Safety Analysis
662 CRASHES IN
SALEM, MA
2022
In 2022, Salem recorded 662 total traffic crashes, a 6.3% increase from the 623 crashes reported in 2021. During this period, the number of fatalities rose from one in 2021 to three in 2022. A notable year-over-year change was the increase in crashes attributed to 'Failed to yield right of way,' which rose from 65 incidents in 2021 to become the leading cause in 2022 with 87 incidents.
662
▲ 6.3%was 623
Total Crash Events
3
▲ 200.0%was 1
Persons Killed
185
▲ 5.1%was 176
Persons Injured
49
▲ 25.6%was 39
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 34 crashes with unreported severity are 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 crashes in Salem trended upward from 2021 to 2022. The total number of crashes increased by 6.3%, from 623 to 662. This rise was accompanied by a 5.1% increase in total injuries (from 176 to 185) and an increase in fatalities from one to three.
49
Hit-and-Run Crashes — 2022
▲ 25.6% vs prior (39)
Hit-and-run incidents increased from 39 in 2021 to 49 in 2022, a 25.6% rise in count. The hit-and-run rate, which measures the proportion of all crashes that are hit-and-runs, also trended upward from 6.3% in 2021 to 7.4% in 2022.
Vulnerable Road User Casualties
1
Pedestrians Killed
2
Motorists Killed
0
Pedestrians Injured
185
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 shifted between the two years. The peak day for collisions moved from Tuesday in 2021 (99 crashes) to Monday in 2022 (112 crashes). The peak hour also shifted earlier, from the 5 p.m. hour in 2021 (52 crashes) to the 3 p.m. hour in 2022 (57 crashes).
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
The severity of crashes increased from 2021 to 2022, with the number of fatal crashes doubling from one to two. Consequently, the fatal crash rate rose from 0.16% to 0.3%. The number of crashes resulting in serious injuries was unchanged at six for both years. While the absolute number of injury-related crashes was similar (131 in 2022 vs. 134 in 2021), their proportion of all crashes decreased slightly from 21.5% to 19.8%.
Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.
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 ranking of top contributing factors changed between periods. 'Failed to yield right of way' became the leading factor in 2022 with 87 incidents, a 33.8% increase in count from 65 incidents in 2021, when it was ranked second. 'No improper driving,' the top factor in 2021 with 93 incidents, decreased to 85 incidents and fell to the second position in 2022. Crashes attributed to 'Followed too closely' increased by 24% in count, from 50 to 62 incidents, remaining the third most common factor.
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
The distribution of crashes across environmental conditions remained largely stable year-over-year. The majority of crashes in both periods occurred in daylight (62.4% in 2022 vs. 68.1% in 2021) and on dry roads (81.6% in 2022 vs. 80.6% in 2021). There was a slight proportional increase in crashes occurring after dark on lighted roadways, which accounted for 31.1% of incidents in 2022 compared to 26.5% in 2021.
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 vehicle makes involved in crashes saw a shift in rankings, with Honda (233 vehicles) overtaking Toyota (205 vehicles) for the top spot in 2022; in 2021, Toyota was first with 202 vehicles. An analysis of persons involved shows a notable increase in the 0-15 age group, which grew from 59 individuals in 2021 to 96 in 2022. The 26-34 age group also saw an increase, rising from 266 to 316 persons involved.
Top Vehicle Makes (1,288 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
146 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,494 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
Crashes appeared to shift toward slightly higher speed zones from 2021 to 2022. While the 25 mph zone had the most crashes in both years, there was a notable increase in incidents in 30 mph zones (from 62 to 90) and 35 mph zones (from 23 to 32). The location of fatal crashes also moved to higher speed zones; the two fatal crashes in 2022 occurred in 35 mph and 45 mph zones, whereas the single fatal crash in 2021 occurred in a 25 mph zone.
Fatal crashes by zone: 35 mph: 1 of 32 (3.125%) · 45 mph: 1 of 4 (25%)
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: SALEM, MA
- Total crash records analyzed: 662
- Total persons involved: 1,642
- Total vehicles involved: 1,288
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: 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/salem/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