Yearly Traffic Safety Analysis

254 CRASHES IN
NANTUCKET, MA
2023

All metrics benchmarked against2022

In 2023, Nantucket recorded 254 total crashes, a 9.5% increase from the 232 crashes reported in 2022. While overall crashes increased, the number of fatalities dropped from one in 2022 to zero in 2023. Crashes where a driver was suspected of being under the influence of alcohol (DUI) increased from 8 incidents in 2022 to 13 in 2023.

254

9.5%was 232

Total Crash Events

0

-100.0%was 1

Persons Killed

52

-7.1%was 56

Persons Injured

36

-7.7%was 39

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. 41 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Nantucket trended upward year-over-year, increasing by 9.5% from 232 incidents in 2022 to 254 in 2023. Despite the rise in total collisions, the number of resulting injuries saw a slight decrease of 7.1%, from 56 in the prior year to 52 in the current year. Fatalities also decreased from one in 2022 to zero in 2023.

36

Hit-and-Run Crashes — 2023

-7.7% vs prior (39)

Hit-and-run incidents showed a downward trend in Nantucket. The total number of hit-and-run crashes decreased from 39 in 2022 to 36 in 2023. Correspondingly, the hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, fell from 16.8% in the prior year to 14.2% in the current year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

0

Other Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 4-50.0%

9

Cyclists Injured

Prior: 650.0%

38

Motorists Injured

Prior: 46-17.4%

3

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained largely consistent between the two years, with collisions peaking during the summer months of June and July. In 2023, crashes were most frequent on Fridays with 44 incidents, the same peak day as in 2022 which had 46 incidents. The peak hour for crashes shifted slightly, moving from 2 p.m. in 2022 (25 crashes) to 1 p.m. in 2023 (28 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity decreased in 2023 compared to the prior year. There were no fatal crashes in 2023, down from one fatal crash in 2022, and no crashes resulted in serious injuries, compared to three in the previous year. The proportion of crashes with no reported injuries increased from 62.1% of all incidents in 2022 to 67.7% in 2023, while the share of crashes involving minor or possible injuries decreased.

Outcome by Severity (Crash Events)

Minor Injury34minor injury crashes13.4%
6.3%prior 32
Possible Injury7possible injury crashes2.8%
-12.5%prior 8
No Injury172no injury crashes67.7%
19.4%prior 144

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors to crashes saw a shift in ranking between 2022 and 2023. While 'No improper driving' remained the most common finding in both years (57 incidents in 2023 vs. 54 in 2022), the second and third positions swapped. Crashes attributed to 'Failed to yield right of way' increased by 30.4% from 23 to 30 incidents, making it the second-leading factor in 2023. Conversely, 'Inattention' as a factor decreased by 32.1% in count, from 28 incidents in 2022 to 19 in 2023.

Officer-Reported Primary Contributing Cause

No improper driving57 (22.4%)5.6%prior 54
Failed to yield right of way30 (11.8%)30.4%prior 23
Inattention19 (7.5%)-32.1%prior 28
Failure to keep in proper lane or running off road13 (5.1%)18.2%prior 11
Followed too closely12 (4.7%)50.0%prior 8
Other improper action12 (4.7%)9.1%prior 11
Exceeded authorized speed limit10 (3.9%)42.9%prior 7
Made an improper turn9 (3.5%)
Visibility obstructed6 (2.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner6 (2.4%)-14.3%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of environmental conditions during crashes was remarkably stable year-over-year. In both 2023 and 2022, the vast majority of crashes occurred in clear weather and on dry road surfaces. Approximately 81% of crashes in both periods happened on dry roads. Similarly, the proportion of crashes occurring during daylight hours remained consistent, accounting for 68.9% of incidents in 2023 compared to 64.7% in 2022.

Weather

Clear/Clear129 (51.0%)
30.3%prior 99
Clear48 (19.0%)
-15.8%prior 57
Cloudy/Cloudy28 (11.1%)
86.7%prior 15
Rain/Rain8 (3.2%)
0.0%prior 8
Cloudy7 (2.8%)
16.7%prior 6
Unknown/Unknown6 (2.4%)
0.0%prior 6
Cloudy/Rain5 (2.0%)
Clear/Cloudy3 (1.2%)
Fog, smog, smoke/Fog, smog, smoke3 (1.2%)
Rain3 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight175 (70.3%)
16.7%prior 150
Dark - roadway not lighted26 (10.4%)
52.9%prior 17
Dark - lighted roadway25 (10.0%)
-30.6%prior 36
Dusk10 (4.0%)
-9.1%prior 11
Dark - unknown roadway lighting9 (3.6%)
Dawn3 (1.2%)
Other1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry208 (84.9%)
10.6%prior 188
Wet22 (9.0%)
0.0%prior 22
Sand, mud, dirt, oil, gravel10 (4.1%)
25.0%prior 8
Other2 (0.8%)
Ice2 (0.8%)
Water (standing, moving)1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained the same in both years, though their order shifted. In 2023, Ford (108 vehicles) became the most common make, surpassing Jeep (69 vehicles), which was the top make in 2022 with 68 vehicles. Regarding persons involved, the 35-44 age group had the highest representation in both periods, although its count decreased from 92 in 2022 to 83 in 2023. Representation for the 55-64 age group saw its involvement increase from 55 to 70 persons.

Top Vehicle Makes (423 vehicles)

1
FORD108 (25.5%)
63.6%prior 66
2
JEEP69 (16.3%)
1.5%prior 68
3
TOYOTA67 (15.8%)
8.1%prior 62
4
CHEVROLET24 (5.7%)
41.2%prior 17
5
HONDA21 (5%)
-8.7%prior 23
6
NISSAN14 (3.3%)
-6.7%prior 15
7
DODGE10 (2.4%)
-9.1%prior 11
8
AUDI9 (2.1%)
80.0%prior 5
9
GMC9 (2.1%)
28.6%prior 7
10
MERCEDES-BENZ6 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (459 persons with recorded sex)

Male302 (65.8%)
21.3%prior 249
Female157 (34.2%)
-4.3%prior 164

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across different speed zones changed between the two periods. In 2022, the 25 mph zone saw the highest number of crashes (26), followed by the 5 mph (23) and 1 mph (21) zones. In 2023, the 5 mph zone was the most frequent location for crashes with 23 incidents, while crashes in the 25 mph zone decreased to 5. The single fatal crash in 2022 occurred in a 45 mph zone; there were no fatal crashes in any speed zone in 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: NANTUCKET, MA
  • Total crash records analyzed: 254
  • Total persons involved: 545
  • Total vehicles involved: 423

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). "NANTUCKET, MA Crash Intelligence Report: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/nantucket/2023-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

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Nantucket, MA Crash Report — 2023 | ThatCarHitMe.com