ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WOBURN, MA · 2025
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/2025-annual-report
Yearly Traffic Safety Analysis
1,042 CRASHES IN
WOBURN, MA
2025
In 2025, Woburn recorded 1,042 total crashes, representing a 5.7% decrease from the 1,105 crashes recorded in 2024. While the overall number of collisions and injuries declined, the most notable year-over-year shift was the increase in total fatalities from 2 to 3. This rise in fatalities occurred despite a general downward trend in most other crash metrics.
1,042
▼ -5.7%was 1,105
Total Crash Events
3
▲ 50.0%was 2
Persons Killed
304
▼ -6.5%was 325
Persons Injured
129
▼ -5.1%was 136
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 32 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, traffic collisions in Woburn showed a downward trend year-over-year, with total crashes decreasing by 5.7% from 1,105 in 2024 to 1,042 in 2025. The number of people injured also declined by 6.5%, from 325 to 304. However, the number of fatalities increased from 2 in the prior year to 3 in the current year.
129
Hit-and-Run Crashes — 2025
▼ -5.1% vs prior (136)
The number of hit-and-run crashes saw a slight decrease, falling from 136 incidents in 2024 to 129 in 2025. Despite the drop in the absolute number of crashes, the hit-and-run rate remained stable. Hit-and-run incidents constituted 12.4% of all crashes in 2025, a negligible change from the 12.3% rate recorded in the previous year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
8
Pedestrians Injured
11
Cyclists Injured
279
Motorists Injured
6
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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, with Thursday being the peak day for collisions in both 2025 (171 crashes) and 2024 (191 crashes). However, the peak hour for crashes shifted later in the day, from the 3 PM hour in 2024 (92 crashes) to the 5 PM hour in 2025 (94 crashes). Crash counts were lower on most days of the week compared to the prior year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes decreased, the fatal crash rate increased from 0.18% in 2024 to 0.29% in 2025, with the count of fatal crashes rising from 2 to 3. Crashes resulting in serious injuries decreased proportionally from 1.5% to 1.2% of all incidents. Conversely, the share of crashes involving minor injuries grew from 13.5% to 15.2% year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes saw a notable shift in ranking between 2024 and 2025. Crashes attributed to 'Failed to yield right of way' increased in count by 23.9%, from 109 to 135 incidents, moving it from the fourth to the third-ranked factor. In contrast, crashes due to 'Followed too closely' decreased in count by 18.8% from 154 to 125, dropping its rank from second to fourth. The count for 'Inattention' remained unchanged at 144 crashes but rose in rank from third to second.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in both periods predominantly occurred in clear conditions on dry roads during daylight hours. In 2025, 73.3% of crashes happened in daylight, a slight proportional increase from 71.9% in 2024. Crashes on dry road surfaces accounted for 81.5% of the total in 2025, compared to 83.2% in the prior year. The proportion of crashes occurring in adverse weather conditions like rain or snow remained a small fraction of the total in both years.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained consistent, with Toyota, Honda, and Ford leading in both periods. The number of Toyotas and Fords in collisions decreased from 358 to 336 and 244 to 191, respectively, while Hondas saw a slight increase from 286 to 296. The age distribution of persons involved in crashes was also stable, with the 26-34 age group being the largest cohort in both 2025 (428 persons) and 2024 (441 persons).
Top Vehicle Makes (2,092 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
288 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,077 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in both years were most prevalent in 30 mph zones, which accounted for 388 incidents (37.6% of crashes with speed data) in 2025, compared to 397 (36.0%) in 2024. There was a decrease in crashes in 55 mph zones, from 166 incidents to 142. Fatal crashes in 2025 were recorded in 25 mph, 30 mph, and 35 mph zones, whereas in 2024, fatalities occurred in 25 mph and 40 mph zones.
Fatal crashes by zone: 25 mph: 1 of 66 (1.515%) · 30 mph: 1 of 388 (0.258%) · 35 mph: 1 of 183 (0.546%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: WOBURN, MA
- Total crash records analyzed: 1,042
- Total persons involved: 2,396
- Total vehicles involved: 2,092
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/woburn/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved