ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · DRACUT, MA · 2023
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/dracut/2023-annual-report
Yearly Traffic Safety Analysis
426 CRASHES IN
DRACUT, MA
2023
In Dracut, total traffic crashes decreased by 12.9% from 489 in 2022 to 426 in 2023. Despite this overall reduction in collisions, the most notable year-over-year shift was a 31.5% decrease in total injuries, from 168 down to 115. However, the number of fatalities increased from one in 2022 to two in 2023.
426
▼ -12.9%was 489
Total Crash Events
2
▲ 100.0%was 1
Persons Killed
115
▼ -31.5%was 168
Persons Injured
29
▲ 16.0%was 25
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 13 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 safety trends in Dracut show a notable improvement year-over-year, with total crashes falling from 489 to 426, a 12.9% reduction. This positive trend is further reflected in a significant 31.5% decrease in the number of injuries, which dropped from 168 to 115. The only metric to move in the opposite direction was fatalities, which increased from one to two.
29
Hit-and-Run Crashes — 2023
▲ 16.0% vs prior (25)
The number of hit-and-run incidents increased from 25 in 2022 to 29 in 2023. This change represents an increase in both the absolute count and the rate of occurrence. The hit-and-run rate as a percentage of all crashes rose from 5.1% in the prior year to 6.8% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
0
Other Killed
2
Pedestrians Injured
2
Cyclists Injured
110
Motorists Injured
1
Other Injured
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 relatively consistent between the two periods. Friday was the peak day for crashes in both 2022 (83 crashes) and 2023 (77 crashes). In 2022, the 4 PM and 5 PM hours were tied for the peak time with 50 crashes each, whereas in 2023, the 5 PM hour was the sole peak with 36 crashes, indicating a lower volume of incidents during the evening commute.
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
While total crashes declined, the number of fatal crashes doubled from one in 2022 to two in 2023, increasing the fatal crash rate from 0.2% to 0.5%. Conversely, the proportion of crashes involving any level of injury (Serious, Minor, or Possible) decreased from 24.3% of all crashes in 2022 to 19.7% in 2023. Consequently, the share of non-injury crashes grew from 71.4% to 76.8% of all incidents.
Outcome by Severity (Crash Events)
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 reported contributing factor in both periods was 'No improper driving', with an identical count of 133 crashes each year. A significant change was observed in crashes attributed to 'Inattention', which fell by 37.8% from a count of 90 in 2022 to 56 in 2023. In contrast, crashes where 'Followed too closely' was a factor increased in count from 13 to 24 year-over-year.
Officer-Reported Primary Contributing Cause
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 crashes across lighting and road surface conditions was largely stable, with most incidents in both years occurring during daylight on dry roads. A notable shift was the decrease in crashes on roads with snow or ice, which fell from 34 incidents in 2022 to 17 in 2023. The share of crashes in clear weather conditions decreased from 75.3% to 68.5%, while the count of crashes in rain remained unchanged at 37 for both years.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
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 were consistent across both years: Honda, Toyota, and Ford. In 2023, Honda (133 vehicles) surpassed Toyota (129 vehicles) as the most frequently involved make, a reversal from 2022 when Toyota led with 142 vehicles. Regarding persons involved, the share of individuals from the 26-34 age group decreased from 19.1% to 15.6%, while the share from the 65+ age group increased from 9.6% to 11.1%.
Top Vehicle Makes (765 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
67 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (869 persons with recorded sex)
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 both 2022 and 2023, the 30 MPH speed zone was the location for the majority of crashes, accounting for 71.0% and 73.5% of incidents with recorded speed limits, respectively. The overall distribution of crashes across different speed zones did not change significantly. In 2023, one fatal crash occurred in a 30 MPH zone and another in a 45 MPH zone, whereas the single fatal crash from 2022 did not have a speed limit associated with it in the data.
Fatal crashes by zone: 30 mph: 1 of 283 (0.353%) · 45 mph: 1 of 24 (4.167%)
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: DRACUT, MA
- Total crash records analyzed: 426
- Total persons involved: 944
- Total vehicles involved: 765
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). "DRACUT, 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/dracut/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved