Monthly Traffic Safety Analysis

11,758 CRASHES IN
MASSACHUSETTS, MA
MAY 2024

All metrics benchmarked againstMay 2023

In May 2024, there were 11,758 total crashes, a 1.7% decrease from the 11,958 crashes recorded in May 2023. While overall crashes and resulting fatalities (29, down from 34) declined, crashes where speeding was a contributing factor saw a notable year-over-year increase. Crashes attributed to 'Driving too fast for conditions' rose 27.4% from 164 to 209 incidents.

11,758

-1.7%was 11,958

Total Crash Events

29

-14.7%was 34

Persons Killed

3,708

-2.4%was 3,800

Persons Injured

1,095

-9.3%was 1,207

Hit-and-Run Crashes

Note: "Persons Killed" (29) counts individual fatalities across all crash events. "Fatal" in the severity table below (27) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 517 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend shows a slight decrease in traffic incidents compared to the same period last year. Total crashes fell by 1.7%, from 11,958 in May 2023 to 11,758 in May 2024. This downward trend was also reflected in casualties, with total fatalities dropping from 34 to 29 and total injuries decreasing from 3,800 to 3,708.

1,095

Hit-and-Run Crashes — May 2024

-9.3% vs prior (1,207)

Hit-and-run incidents decreased in both absolute numbers and as a percentage of total crashes. In May 2024, there were 1,095 hit-and-run crashes, down from 1,207 in May 2023. This represents a downward trend in the hit-and-run rate, which fell from 10.1% to 9.3% of all crashes year-over-year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 5-80.0%

2

Cyclists Killed

Prior: 0%

25

Motorists Killed

Prior: 28-10.7%

1

Other Killed

Prior: 10.0%

106

Pedestrians Injured

Prior: 122-13.1%

144

Cyclists Injured

Prior: 1412.1%

3,424

Motorists Injured

Prior: 3,519-2.7%

34

Other Injured

Prior: 1888.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak hour for crashes remained the 3 p.m. hour in both periods, with 1,028 incidents in May 2024 compared to 1,069 in May 2023. However, the peak day for crashes shifted from Wednesday (1,953 crashes) in the prior year to Friday (2,168 crashes) in the current period. Weekday patterns also changed, with crashes on Thursday and Friday increasing year-over-year, while incidents on Monday through Wednesday decreased.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity profiles shifted slightly year-over-year, with a greater proportion of incidents resulting in no injury. The share of no-injury crashes increased from 69.8% in May 2023 to 71.7% in May 2024. Correspondingly, the fatal crash count decreased from 32 to 27, and the share of fatal crashes fell from 0.3% to 0.2% of the total. The proportion of serious injury crashes remained stable at 1.8% across both periods.

Severity is per crash event (most severe injury). 27 fatal crash events resulted in 29 persons killed.

Outcome by Severity (Crash Events)

Fatal27fatal crashes0.2%
-15.6%prior 32
Serious Injury212serious injury crashes1.8%
-0.9%prior 214
Minor Injury1,715minor injury crashes14.6%
0.8%prior 1,702
Possible Injury857possible injury crashes7.3%
-4.2%prior 895
No Injury8,430no injury crashes71.7%
1.0%prior 8,346

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Most severe injury per crash record

Top Contributing Factors

The top three contributing factors remained consistent year-over-year: 'No improper driving,' 'Inattention,' and 'Failed to yield right of way.' While the count of crashes attributed to 'Inattention' decreased by 3.3% (from 1,752 to 1,694), incidents involving speed-related factors grew. Crashes attributed to 'Driving too fast for conditions' increased in count by 27.4% from 164 to 209, and those for 'Exceeded authorized speed limit' rose in count by 12.7% from 134 to 151.

Officer-Reported Primary Contributing Cause

No improper driving2,786 (23.7%)2.8%prior 2,710
Inattention1,694 (14.4%)-3.3%prior 1,752
Failed to yield right of way1,335 (11.4%)0.3%prior 1,331
Followed too closely1,152 (9.8%)0.0%prior 1,152
Failure to keep in proper lane or running off road538 (4.6%)0.6%prior 535
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner387 (3.3%)-2.0%prior 395
Other improper action380 (3.2%)1.3%prior 375
Disregarded traffic signs, signals, road markings347 (3%)14.1%prior 304
Distracted288 (2.4%)-2.7%prior 296
Driving too fast for conditions209 (1.8%)27.4%prior 164

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in adverse weather and road conditions increased compared to the previous year. In May 2024, 14.6% of crashes occurred on wet road surfaces, up from 8.9% in May 2023. Correspondingly, crashes during rain increased from 4.5% to 7.2% of the total. Crashes in daylight conditions remained the dominant scenario, accounting for approximately 79% of all incidents in both periods.

Weather

Clear7,928 (68.6%)
-11.3%prior 8,939
Cloudy1,002 (8.7%)
70.7%prior 587
Rain844 (7.3%)
58.1%prior 534
Clear/Clear684 (5.9%)
-21.0%prior 866
Cloudy/Rain339 (2.9%)
96.0%prior 173
Clear/Cloudy208 (1.8%)
13.7%prior 183
Rain/Cloudy125 (1.1%)
60.3%prior 78
Clear/Unknown96 (0.8%)
-7.7%prior 104
Clear/Other92 (0.8%)
-5.2%prior 97
Cloudy/Cloudy57 (0.5%)
78.1%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Weather condition at time of crash

Lighting

Daylight9,249 (79.6%)
-1.6%prior 9,398
Dark - lighted roadway1,449 (12.5%)
-5.3%prior 1,530
Dark - roadway not lighted441 (3.8%)
0.9%prior 437
Dusk235 (2.0%)
-14.5%prior 275
Dawn169 (1.5%)
33.1%prior 127
Dark - unknown roadway lighting66 (0.6%)
40.4%prior 47
Other10 (0.1%)
66.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Lighting condition field

Road Surface

Dry9,802 (84.9%)
-8.4%prior 10,697
Wet1,713 (14.8%)
59.9%prior 1,071
Sand, mud, dirt, oil, gravel19 (0.2%)
-20.8%prior 24
Water (standing, moving)7 (0.1%)
40.0%prior 5
Other6 (0.1%)
Snow2 (0.0%)
Reported but invalid1 (0.0%)
-85.7%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—were consistent across both periods, maintaining their rank order. The number of Toyotas involved in crashes increased from 3,574 to 3,716, while Fords decreased from 2,417 to 2,296. The age distribution of persons involved in crashes also remained stable, with the 26-34 age group being the most frequently involved in both May 2024 (4,506 persons) and May 2023 (4,650 persons).

Top Vehicle Makes (22,183 vehicles)

1
TOYOTA3,716 (16.8%)
4.0%prior 3,574
2
HONDA2,916 (13.1%)
0.4%prior 2,905
3
FORD2,296 (10.4%)
-5.0%prior 2,417
4
CHEVROLET1,506 (6.8%)
-1.1%prior 1,522
5
NISSAN1,340 (6%)
-9.2%prior 1,476
6
JEEP1,073 (4.8%)
3.8%prior 1,034
7
SUBARU867 (3.9%)
3.7%prior 836
8
HYUNDAI850 (3.8%)
-0.8%prior 857
9
KIA537 (2.4%)
-0.9%prior 542
10
GMC465 (2.1%)
-0.2%prior 466

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Vehicle unit records

2,768 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (24,618 persons with recorded sex)

Male13,890 (56.4%)
1.9%prior 13,631
Female10,718 (43.5%)
-2.5%prior 10,996
X / Unspecified10 (0.0%)
-23.1%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across different speed zones remained largely similar, with 30 mph zones accounting for the most incidents in both periods (3,235 in May 2024 vs. 3,205 in May 2023). However, there was a notable shift in where fatal crashes occurred. In May 2024, there were 4 fatal crashes in 45 mph zones, compared to zero in the prior year. Similarly, the number of fatal crashes in 65 mph zones increased from 2 to 6.

Fatal crashes by zone: 25 mph: 3 of 2,533 (0.118%) · 30 mph: 6 of 3,235 (0.185%) · 35 mph: 2 of 1,449 (0.138%) · 40 mph: 2 of 835 (0.24%) · 45 mph: 4 of 403 (0.993%) · 50 mph: 2 of 266 (0.752%) · 55 mph: 1 of 550 (0.182%) · 60 mph: 1 of 67 (1.493%) · 65 mph: 6 of 792 (0.758%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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: 2024-05-01 through 2024-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-05-01 through 2024-05-31 (31 days)
  • Geographic scope: massachusetts, MA
  • Total crash records analyzed: 11,758
  • Total persons involved: 27,744
  • Total vehicles involved: 22,183

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). "massachusetts, MA Crash Intelligence Report: May 2024." Published June 21, 2026. Reporting period: 2024-05-01 to 2024-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/statewide/may-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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Massachusetts (Statewide) Crash Report — May 2024 | ThatCarHitMe.com