ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WOBURN, MA · 2024
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/2024-annual-report
Yearly Traffic Safety Analysis
1,105 CRASHES IN
WOBURN, MA
2024
In 2024, Woburn recorded 1,105 total crashes, a 7.9% increase from the 1,024 crashes in 2023. Total injuries rose by 12.8% from 288 to 325, while fatalities remained stable at two. A notable year-over-year shift was the 21.4% increase in the number of hit-and-run incidents, which rose from 112 to 136.
1,105
▲ 7.9%was 1,024
Total Crash Events
2
Persons Killed
325
▲ 12.8%was 288
Persons Injured
136
▲ 21.4%was 112
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. 35 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crash trends in Woburn are rising. Total crashes increased by 7.9% from 1,024 in 2023 to 1,105 in 2024. Similarly, the number of people injured rose by 12.8%, from 288 to 325. The number of fatalities, however, remained unchanged at two for both years.
136
Hit-and-Run Crashes — 2024
▲ 21.4% vs prior (112)
Hit-and-run incidents showed an upward trend in 2024 compared to the previous year. The total count of hit-and-run crashes increased by 21.4%, rising from 112 in 2023 to 136 in 2024. The hit-and-run rate, which measures these incidents as a percentage of all crashes, also rose from 10.9% to 12.3%.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
0
Other Killed
11
Pedestrians Injured
9
Cyclists Injured
303
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed a slight shift between the two periods. In 2024, the peak day for crashes was Thursday with 191 incidents, a change from Wednesday (172 incidents) in the prior year. The peak hour also shifted earlier, from 4 p.m. in 2023 (102 crashes) to 3 p.m. in 2024 (92 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the number of fatal crashes remained stable at two in both 2024 and 2023, the severity of non-fatal crashes increased. The count of serious injury crashes rose from 13 to 17, and minor injury crashes increased from 117 to 149. Consequently, the share of crashes resulting in a serious or minor injury grew from 12.7% of all crashes in 2023 to 15.0% in 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors for crashes saw a shift in ranking year-over-year. While 'No improper driving' remained the most cited factor, 'Followed too closely' moved up to the second position in 2024 with 154 crashes, a 26.2% increase in count from 122 in 2023. Conversely, 'Inattention' dropped to third place, with its count decreasing by 13.8% from 167 to 144 crashes. 'Failed to yield right of way' remained the fourth-leading factor in both years, with a small increase in count from 105 to 109.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Compared to the prior year, a larger proportion of crashes in 2024 occurred in clear weather and on dry roads. Crashes on dry road surfaces constituted 83.2% of the total in 2024, up from a 79.2% share in 2023. Similarly, the share of crashes happening in clear weather increased from 69.0% to 74.9%. The proportion of crashes in daylight conditions remained relatively stable, accounting for 71.9% of crashes in 2024 versus 69.8% in 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained unchanged in their ranking between 2023 and 2024. Analysis of persons involved shows a shift in age distribution, with the 21-25 age group's representation increasing from 8.9% of all persons in 2023 to 10.5% in 2024. In contrast, the share of persons in the 16-20 age group decreased from 9.1% to 7.8% over the same period.
Top Vehicle Makes (2,186 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
260 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,193 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones shifted slightly in 2024. The proportion of crashes in 30 MPH zones, the most common zone for incidents, decreased from a 39.7% share in 2023 to 36.1% in 2024. This was offset by increases in the share of crashes in 35 MPH zones (from 17.4% to 19.1%) and 55 MPH zones (from 12.7% to 15.1%). The two fatal crashes in 2024 occurred in 25 MPH and 40 MPH zones, different from the 35 MPH and 65 MPH zones where fatalities were recorded in 2023.
Fatal crashes by zone: 25 mph: 1 of 78 (1.282%) · 40 mph: 1 of 32 (3.125%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: WOBURN, MA
- Total crash records analyzed: 1,105
- Total persons involved: 2,493
- Total vehicles involved: 2,186
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/woburn/2024-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved