Yearly Traffic Safety Analysis

190 CRASHES IN
DUDLEY, MA
2023

All metrics benchmarked against2022

In 2023, Dudley experienced 190 total vehicle crashes, an 10.5% increase from the 172 crashes recorded in 2022. While total fatalities remained stable at one death in each year, total injuries rose from 57 to 67. The most significant year-over-year shift was the number of crashes involving a driver suspected of being under the influence of alcohol, which more than doubled from 5 to 11 incidents.

190

10.5%was 172

Total Crash Events

1

Persons Killed

67

17.5%was 57

Persons Injured

6

50.0%was 4

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 3 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

Overall, crash trends in Dudley are rising year-over-year. Total crashes increased by 10.5% from 172 in 2022 to 190 in 2023. The number of people injured in these incidents also grew by 17.5%, from 57 to 67, while the number of fatalities held steady at one for both years.

6

Hit-and-Run Crashes — 2023

50.0% vs prior (4)

Hit-and-run incidents increased from 4 in 2022 to 6 in 2023, representing a 50% rise in count. This upward trend is also reflected in the hit-and-run rate, which measures the proportion of all crashes that were hit-and-runs. The rate increased from 2.3% in 2022 to 3.2% in 2023.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 10.0%

1

Pedestrians Injured

Prior: 0%

1

Cyclists Injured

Prior: 10.0%

65

Motorists Injured

Prior: 5616.1%

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 peak hour for crashes was consistent year-over-year, occurring at 2 p.m. with 19 incidents in both 2022 and 2023. However, the peak day for crashes shifted from Tuesday (35 crashes) in 2022 to a tie between Wednesday and Friday in 2023, with each day recording 32 crashes. This reflects an increase in crash counts for both Wednesday (from 27 to 32) and Friday (from 25 to 32).

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

The number of fatal crashes remained unchanged at one incident in both 2023 and 2022, leading to a slight decrease in the fatal crash rate from 0.58% to 0.53% of all crashes. The proportion of crashes resulting in any level of injury (Serious, Minor, or Possible) decreased from 26.7% in 2022 to 21.6% in 2023. Consequently, the share of non-injury crashes increased, accounting for 76.3% of all incidents in 2023 compared to 68.6% in the prior year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.5%
0.0%prior 1
Serious Injury2serious injury crashes1.1%
-33.3%prior 3
Minor Injury30minor injury crashes15.8%
-3.2%prior 31
Possible Injury9possible injury crashes4.7%
-25.0%prior 12
No Injury145no injury crashes76.3%
22.9%prior 118

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 were consistent across both periods, with "No improper driving" (49 crashes in 2023 vs. 43 in 2022) and "Inattention" (34 vs. 33) ranking as the top two. A notable increase was observed in crashes attributed to "Failure to keep in proper lane or running off road," where the count grew from 2 incidents in 2022 to 7 in 2023. In contrast, crashes linked to an "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" saw a small decrease in count from 13 to 11.

Officer-Reported Primary Contributing Cause

No improper driving49 (25.8%)14.0%prior 43
Inattention34 (17.9%)3.0%prior 33
Failed to yield right of way16 (8.4%)-5.9%prior 17
Followed too closely12 (6.3%)20.0%prior 10
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner11 (5.8%)-15.4%prior 13
Distracted8 (4.2%)33.3%prior 6
Failure to keep in proper lane or running off road7 (3.7%)
Visibility obstructed5 (2.6%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway4 (2.1%)
Glare3 (1.6%)

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

Crashes on dry road surfaces increased from 122 in 2022 to 151 in 2023, while incidents on non-dry surfaces like wet, snow, or ice decreased from 49 to 39. This marks a proportional shift, as crashes on adverse road surfaces accounted for 20.5% of the total in 2023, down from 28.5% in 2022. The majority of crashes in both years occurred during daylight, with 131 incidents in 2023 compared to 113 in 2022.

Weather

Clear103 (54.2%)
15.7%prior 89
Cloudy18 (9.5%)
20.0%prior 15
Clear/Other17 (8.9%)
30.8%prior 13
Clear/Unknown13 (6.8%)
30.0%prior 10
Rain13 (6.8%)
85.7%prior 7
Cloudy/Rain5 (2.6%)
Clear/Cloudy5 (2.6%)
Snow/Sleet, hail (freezing rain or drizzle)3 (1.6%)
-40.0%prior 5
Fog, smog, smoke2 (1.1%)
Cloudy/Unknown2 (1.1%)

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

Lighting

Daylight131 (68.9%)
15.9%prior 113
Dark - lighted roadway39 (20.5%)
-7.1%prior 42
Dark - roadway not lighted8 (4.2%)
0.0%prior 8
Dusk5 (2.6%)
Dawn3 (1.6%)
Dark - unknown roadway lighting3 (1.6%)
Other1 (0.5%)

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

Road Surface

Dry151 (79.5%)
23.8%prior 122
Wet32 (16.8%)
45.5%prior 22
Snow3 (1.6%)
-80.0%prior 15
Ice2 (1.1%)
-81.8%prior 11
Sand, mud, dirt, oil, gravel1 (0.5%)
Slush1 (0.5%)

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 showed a slight change in ranking between the two years. In 2023, the top makes were Toyota (67 vehicles), Ford (50), and Honda (30), whereas in 2022 the order was Toyota (44), Honda (36), and Ford (30). Regarding persons involved, the 26-34 age group was the most represented in both years, with its count increasing from 64 persons in 2022 to 70 in 2023.

Top Vehicle Makes (330 vehicles)

1
TOYOTA67 (20.3%)
52.3%prior 44
2
FORD50 (15.2%)
66.7%prior 30
3
HONDA30 (9.1%)
-16.7%prior 36
4
CHEVROLET27 (8.2%)
17.4%prior 23
5
NISSAN22 (6.7%)
15.8%prior 19
6
HYUNDAI21 (6.4%)
133.3%prior 9
7
JEEP15 (4.5%)
-28.6%prior 21
8
SUBARU14 (4.2%)
-12.5%prior 16
9
MAZDA6 (1.8%)
-14.3%prior 7
10
GMC6 (1.8%)
-40.0%prior 10

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

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

Sex Distribution (388 persons with recorded sex)

Male208 (53.6%)
17.5%prior 177
Female180 (46.4%)
13.2%prior 159

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

In 2023, the most crashes occurred in 35 mph zones (52 incidents), a shift from 2022 when 40 mph zones had the highest frequency (38 incidents). The single fatal crash in 2023 took place in a 40 mph zone. This differs from the prior year, where the fatal crash occurred in a 45 mph zone.

Fatal crashes by zone: 40 mph: 1 of 37 (2.703%)

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: DUDLEY, MA
  • Total crash records analyzed: 190
  • Total persons involved: 424
  • Total vehicles involved: 330

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). "DUDLEY, 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/dudley/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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