Monthly Traffic Safety Analysis

45 CRASHES IN
SALEM, MA
AUGUST 2024

All metrics benchmarked againstAugust 2023

In August 2024, Salem, MA experienced 45 total crashes, a 6.25% decrease compared to the 48 crashes reported in August 2023. The most significant year-over-year shift was the reduction in fatalities, decreasing from 1 in the prior period to 0 in the current period. Total injuries, however, saw an increase from 16 to 19.

45

-6.3%was 48

Total Crash Events

0

-100.0%was 1

Persons Killed

19

18.8%was 16

Persons Injured

1

-50.0%was 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. 5 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in Salem, MA showed a slight downward trend, decreasing by 3 crashes or 6.25% year-over-year. Fatalities were eliminated entirely, dropping from 1 to 0, while injuries increased by 3, an 18.75% rise.

1

Hit-and-Run Crashes — August 2024

-50.0% vs prior (2)

Hit-and-run crashes decreased from 2 in the prior period to 1 in the current period, representing a 50% reduction in count. The hit-and-run rate also decreased, dropping from 4.2% to 2.2% year-over-year.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

4

Cyclists Injured

Prior: 40.0%

15

Motorists Injured

Prior: 1136.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Thursday in both periods, with 10 crashes recorded. However, the peak hour for crashes shifted from 3 PM with 7 crashes in the prior period to 4 PM with 10 crashes in the current period. Monday crashes increased from 6 to 8, while Sunday crashes decreased from 7 to 2.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 1 in the prior period to 0 in the current period, eliminating the 2.1% fatal crash rate. While minor injury crashes decreased from 10 to 8, possible injury crashes increased from 5 to 7. The proportion of crashes resulting in no injury decreased from 60.4% to 55.6%.

Outcome by Severity (Crash Events)

Minor Injury8minor injury crashes17.8%
-20.0%prior 10
Possible Injury7possible injury crashes15.6%
40.0%prior 5
No Injury25no injury crashes55.6%
-13.8%prior 29

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'Failed to yield right of way,' saw a slight decrease from 9 crashes in the prior period to 8 in the current period. 'No improper driving' also decreased from 5 crashes to 4. Conversely, 'Failure to keep in proper lane or running off road' increased from 1 crash to 4 crashes, representing a 300% increase in count.

Officer-Reported Primary Contributing Cause

Failed to yield right of way8 (17.8%)-11.1%prior 9
Failure to keep in proper lane or running off road4 (8.9%)
No improper driving4 (8.9%)-20.0%prior 5
Disregarded traffic signs, signals, road markings3 (6.7%)
Inattention3 (6.7%)
Followed too closely2 (4.4%)
Distracted2 (4.4%)
Driving too fast for conditions2 (4.4%)
Other improper action2 (4.4%)
Over-correcting/over-steering1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear/Clear' weather conditions decreased from 35 to 32, while 'Rain/Rain' conditions saw a decrease from 3 crashes to 1. Crashes during daylight hours increased from 34 to 39, whereas crashes in 'Dark - lighted roadway' conditions decreased from 11 to 6. Crashes on wet road surfaces decreased from 3 to 1.

Weather

Clear/Clear32 (71.1%)
-8.6%prior 35
Clear8 (17.8%)
33.3%prior 6
Clear/Cloudy3 (6.7%)
Fog, smog, smoke/Cloudy1 (2.2%)
Rain/Rain1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Weather condition at time of crash

Lighting

Daylight39 (86.7%)
14.7%prior 34
Dark - lighted roadway6 (13.3%)
-45.5%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Lighting condition field

Road Surface

Dry44 (97.8%)
0.0%prior 44
Wet1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Road surface condition field

Vehicles & Demographics

TOYOTA vehicles involved in crashes increased from 14 to 23, while HONDA vehicles decreased from 16 to 12. The 0-15 age group saw an increase in persons involved in crashes from 7 to 12, and the 65+ age group increased from 9 to 15. Conversely, the 16-20 age group decreased from 10 to 4, and the 55-64 age group decreased from 17 to 8.

Top Vehicle Makes (85 vehicles)

1
TOYOTA23 (27.1%)
64.3%prior 14
2
HONDA12 (14.1%)
-25.0%prior 16
3
FORD8 (9.4%)
-11.1%prior 9
4
HYUNDAI8 (9.4%)
14.3%prior 7
5
NISSAN5 (5.9%)
6
CHEVROLET4 (4.7%)
7
JEEP4 (4.7%)
-42.9%prior 7
8
SUBARU4 (4.7%)
9
HD2 (2.4%)
10
MAZDA2 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Vehicle unit records

7 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (108 persons with recorded sex)

Female57 (52.8%)
5.6%prior 54
Male51 (47.2%)
8.5%prior 47

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 MPH speed zone remained constant at 22 crashes in both periods, though the prior period recorded 1 fatal crash in this zone while the current period recorded none. Crashes in the 30 MPH zone decreased from 6 to 2. New speed zones with crashes observed in the current period include 35 MPH (2 crashes), 40 MPH (1 crash), and 45 MPH (1 crash).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · 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: 2024-08-01 through 2024-08-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-08-01 through 2024-08-31 (31 days)
  • Geographic scope: SALEM, MA
  • Total crash records analyzed: 45
  • Total persons involved: 114
  • Total vehicles involved: 85

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: August 2024." Published June 21, 2026. Reporting period: 2024-08-01 to 2024-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/salem/august-2024-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

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Salem, MA Crash Report — August 2024 | ThatCarHitMe.com