Monthly Traffic Safety Analysis

11,958 CRASHES IN
MASSACHUSETTS, MA
MAY 2023

All metrics benchmarked againstMay 2022

In May 2023, there were 11,958 total crashes, a 6.1% increase from the 11,271 crashes recorded in May 2022. While total crashes and the number of people injured both rose, the number of fatalities decreased from 43 to 34 year-over-year. One of the most notable shifts was a 32.3% increase in the number of hit-and-run crashes, which grew from 912 to 1,207.

11,958

6.1%was 11,271

Total Crash Events

34

-20.9%was 43

Persons Killed

3,800

6.1%was 3,582

Persons Injured

1,207

32.3%was 912

Hit-and-Run Crashes

Note: "Persons Killed" (34) counts individual fatalities across all crash events. "Fatal" in the severity table below (32) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 769 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash volume increased in May 2023 compared to the same month in the prior year. Total crashes rose by 6.1% from 11,271 to 11,958, and the number of injuries saw a similar 6.1% increase from 3,582 to 3,800. In contrast, the number of fatalities decreased by 20.9%, from 43 in May 2022 to 34 in May 2023.

1,207

Hit-and-Run Crashes — May 2023

32.3% vs prior (912)

The number of hit-and-run incidents increased significantly in May 2023 compared to May 2022. The total count of hit-and-run crashes rose by 32.3%, from 912 to 1,207. This represents a clear upward trend, as the rate of hit-and-runs as a percentage of all crashes also increased from 8.1% to 10.1% year-over-year.

Vulnerable Road User Casualties

5

Pedestrians Killed

Prior: 11-54.5%

0

Cyclists Killed

Prior: 1-100.0%

28

Motorists Killed

Prior: 31-9.7%

1

Other Killed

Prior: 0%

122

Pedestrians Injured

Prior: 9627.1%

141

Cyclists Injured

Prior: 11423.7%

3,519

Motorists Injured

Prior: 3,3614.7%

18

Other Injured

Prior: 1163.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between May 2022 and May 2023. The peak day for crashes moved from Tuesday (1,850 crashes) in the prior period to Wednesday (1,953 crashes) in the current period. However, the peak hour for collisions remained consistent at the 3 p.m. hour, with crash counts in that time slot increasing from 966 to 1,069 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes shifted slightly in May 2023 compared to the prior year. The number of fatal crashes decreased from 40 to 32, and the share of crashes resulting in a fatality dropped from 0.4% to 0.3%. Crashes involving minor injuries increased in both count (from 1,484 to 1,702) and share of total crashes (from 13.2% to 14.2%), as did the proportion of non-injury crashes.

Severity is per crash event (most severe injury). 32 fatal crash events resulted in 34 persons killed.

Outcome by Severity (Crash Events)

Fatal32fatal crashes0.3%
-20.0%prior 40
Serious Injury214serious injury crashes1.8%
-7.8%prior 232
Minor Injury1,702minor injury crashes14.2%
14.7%prior 1,484
Possible Injury895possible injury crashes7.5%
1.4%prior 883
No Injury8,346no injury crashes69.8%
9.6%prior 7,615

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors to crashes remained consistent year-over-year, with "Inattention" and "Failed to yield right of way" being the top two driver-related causes in both periods. However, the number of crashes attributed to these factors increased. Crashes involving inattention rose by 7.7% in count from 1,627 to 1,752, while those where a driver failed to yield the right of way increased by 16.1% in count from 1,146 to 1,331. Similarly, the count of crashes due to following too closely grew by 13.6% from 1,014 to 1,152.

Officer-Reported Primary Contributing Cause

No improper driving2,710 (22.7%)6.6%prior 2,542
Inattention1,752 (14.7%)7.7%prior 1,627
Failed to yield right of way1,331 (11.1%)16.1%prior 1,146
Followed too closely1,152 (9.6%)13.6%prior 1,014
Failure to keep in proper lane or running off road535 (4.5%)10.8%prior 483
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner395 (3.3%)-3.2%prior 408
Other improper action375 (3.1%)-6.7%prior 402
Disregarded traffic signs, signals, road markings304 (2.5%)7.4%prior 283
Distracted296 (2.5%)-4.5%prior 310
Made an improper turn175 (1.5%)12.2%prior 156

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained largely stable between May 2022 and May 2023. In both periods, the vast majority of crashes occurred in daylight (78.6% in 2023 vs. 76.8% in 2022) and on dry road surfaces (89.5% in 2023 vs. 90.2% in 2022). There were no significant year-over-year shifts in the proportions of crashes occurring during adverse lighting or road surface conditions.

Weather

Clear8,939 (76.1%)
10.9%prior 8,061
Clear/Clear866 (7.4%)
11.5%prior 777
Cloudy587 (5.0%)
-38.4%prior 953
Rain534 (4.5%)
39.1%prior 384
Clear/Cloudy183 (1.6%)
-12.4%prior 209
Cloudy/Rain173 (1.5%)
-13.5%prior 200
Clear/Unknown104 (0.9%)
8.3%prior 96
Clear/Other97 (0.8%)
-15.7%prior 115
Rain/Cloudy78 (0.7%)
4.0%prior 75
Rain/Rain50 (0.4%)
85.2%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash

Lighting

Daylight9,398 (79.5%)
8.5%prior 8,660
Dark - lighted roadway1,530 (12.9%)
-4.1%prior 1,595
Dark - roadway not lighted437 (3.7%)
-9.5%prior 483
Dusk275 (2.3%)
21.1%prior 227
Dawn127 (1.1%)
-0.8%prior 128
Dark - unknown roadway lighting47 (0.4%)
-9.6%prior 52
Other6 (0.1%)
-45.5%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field

Road Surface

Dry10,697 (90.6%)
5.2%prior 10,164
Wet1,071 (9.1%)
12.6%prior 951
Sand, mud, dirt, oil, gravel24 (0.2%)
26.3%prior 19
Reported but invalid7 (0.1%)
Water (standing, moving)5 (0.0%)
Other4 (0.0%)
-33.3%prior 6
Snow2 (0.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained the same in May 2023 as in the prior year, with counts for each increasing in line with the overall rise in crashes. An analysis of persons involved shows a slight shift in age demographics. The proportion of individuals aged 65 and older involved in crashes increased from 10.0% of all persons in May 2022 to 10.8% in May 2023.

Top Vehicle Makes (22,427 vehicles)

1
TOYOTA3,574 (15.9%)
4.7%prior 3,415
2
HONDA2,905 (13%)
8.0%prior 2,690
3
FORD2,417 (10.8%)
9.0%prior 2,218
4
CHEVROLET1,522 (6.8%)
8.6%prior 1,401
5
NISSAN1,476 (6.6%)
6.0%prior 1,392
6
JEEP1,034 (4.6%)
5.1%prior 984
7
HYUNDAI857 (3.8%)
10.3%prior 777
8
SUBARU836 (3.7%)
8.0%prior 774
9
KIA542 (2.4%)
30.6%prior 415
10
VOLKSWAGEN473 (2.1%)
29.2%prior 366

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records

3,266 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (24,640 persons with recorded sex)

Male13,631 (55.3%)
7.5%prior 12,680
Female10,996 (44.6%)
9.8%prior 10,012
X / Unspecified13 (0.1%)
62.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across different speed zones was similar year-over-year, with the highest volumes occurring in 25 mph and 30 mph zones in both periods. Crashes in 25 mph zones increased by 13.9% from 2,091 to 2,381, while the number of fatal crashes in that zone remained unchanged at 6. In 30 mph zones, total crashes were stable (3,174 vs. 3,205), but the number of fatal crashes fell from 10 to 6.

Fatal crashes by zone: 20 mph: 1 of 369 (0.271%) · 25 mph: 6 of 2,381 (0.252%) · 30 mph: 6 of 3,205 (0.187%) · 35 mph: 7 of 1,493 (0.469%) · 40 mph: 5 of 842 (0.594%) · 50 mph: 1 of 254 (0.394%) · 55 mph: 2 of 580 (0.345%) · 65 mph: 2 of 775 (0.258%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-05-01 through 2023-05-31 (31 days)
  • Geographic scope: massachusetts, MA
  • Total crash records analyzed: 11,958
  • Total persons involved: 28,352
  • Total vehicles involved: 22,427

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 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/statewide/may-2023-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 2023 | ThatCarHitMe.com