ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WOBURN, MA · NOVEMBER 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/woburn/november-2023-report
Monthly Traffic Safety Analysis
96 CRASHES IN
WOBURN, MA
NOVEMBER 2023
Total crashes in Woburn increased by 2, from 94 in November 2022 to 96 in November 2023, representing a 2.1% rise. Concurrently, total injuries decreased by 8, from 31 to 23, marking a 25.8% reduction year-over-year.
96
▲ 2.1%was 94
Total Crash Events
0
Persons Killed
23
▼ -25.8%was 31
Persons Injured
10
▲ 42.9%was 7
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. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the number of crashes in Woburn remained relatively stable, with a slight increase of 2 crashes (2.1%) from 94 to 96. Despite this small increase in crash volume, the total number of injuries decreased by 25.8%, falling from 31 injuries in the prior period to 23 in the current period.
10
Hit-and-Run Crashes — November 2023
▲ 42.9% vs prior (7)
Hit-and-run crashes increased from 7 in November 2022 to 10 in November 2023. This change led to an increase in the hit-and-run rate from 7.4% to 10.4% of all crashes.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
0
Other Killed
1
Pedestrians Injured
21
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Tuesday in November 2022, with 20 crashes, to Thursday in November 2023, also with 20 crashes. The peak hour remained consistent at 5 PM in both periods, with 12 crashes each.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both November 2022 and November 2023. Serious injury crashes (severity 'A') also remained stable at 1 crash in both periods. Minor injury crashes (severity 'B') decreased from 14 (14.9% share) to 9 (9.4% share), while possible injury crashes (severity 'C') increased from 9 (9.6% share) to 10 (10.4% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'Failed to yield right of way' saw a significant increase in count, rising from 0 crashes in November 2022 to 11 crashes in November 2023. 'Inattention' also increased from 10 crashes to 15 crashes, while 'Followed too closely' decreased from 17 crashes to 11 crashes. 'No improper driving' decreased slightly from 30 crashes to 29 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained largely consistent year-over-year. Crashes occurring in Daylight increased from 52 to 58, while those in Dark - roadway not lighted conditions decreased from 4 to 1. The number of crashes on dry road surfaces increased slightly from 80 to 81, and crashes during rainy weather increased from 8 to 9.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 187 to 198. Honda became the most frequently involved make, increasing from 23 to 31 vehicles, while Toyota involvement decreased from 35 to 27 vehicles. Regarding persons involved, the 21-25 age group saw a notable increase from 18 to 31 persons, and the 65+ age group decreased from 31 to 20 persons.
Top Vehicle Makes (198 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Vehicle unit records
16 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (199 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph speed zones increased from 35 to 42, representing the highest concentration of crashes in both periods. Conversely, crashes in 35 mph zones decreased from 22 to 17. Crashes at 20 mph zones also decreased from 6 to 3, while crashes at 55 mph zones saw a slight increase from 14 to 15.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-11-01 through 2023-11-30 (30 days)
- Geographic scope: WOBURN, MA
- Total crash records analyzed: 96
- Total persons involved: 220
- Total vehicles involved: 198
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). "WOBURN, MA Crash Intelligence Report: November 2023." Published June 21, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/woburn/november-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-11-01 – 2023-11-30
Generated: June 21, 2026 · All rights reserved