ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WOBURN, MA · OCTOBER 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/october-2024-report
Monthly Traffic Safety Analysis
101 CRASHES IN
WOBURN, MA
OCTOBER 2024
In October 2024, WOBURN recorded 101 crashes, a 3.06% increase from the 98 crashes reported in October 2023. A notable shift includes the rise in DUI-related crashes from 0 to 2 year-over-year. Total injuries decreased from 35 to 32, while fatalities remained at zero for both periods.
101
▲ 3.1%was 98
Total Crash Events
0
Persons Killed
32
▼ -8.6%was 35
Persons Injured
10
▼ -16.7%was 12
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the number of crashes in WOBURN saw a slight increase year-over-year, rising by 3.06% from 98 crashes in October 2023 to 101 crashes in October 2024. This indicates a stable to slightly increasing trend in crash incidents. Despite the increase in total crashes, total injuries decreased from 35 to 32.
10
Hit-and-Run Crashes — October 2024
▼ -16.7% vs prior (12)
The number of hit-and-run crashes decreased from 12 in October 2023 to 10 in October 2024. The hit-and-run rate also saw a decline, moving from 12.2% of all crashes in the prior period to 9.9% in the current period. This indicates a downward trend in hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
31
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · 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 Wednesday in October 2023 (22 crashes) to Tuesday in October 2024 (22 crashes), maintaining the same crash count for the peak day. The peak hour also shifted from 3 PM (10 crashes) in the prior period to 5 PM (11 crashes) in the current period, indicating a later afternoon peak for crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Both October 2023 and October 2024 reported no fatalities or fatal crashes. Total injuries decreased from 35 in the prior period to 32 in the current period. The proportion of minor injury crashes decreased from 17.3% to 12.9%, while 'No Injury' crashes increased from 65.3% to 73.3% year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'No improper driving' saw an increase from 23 crashes in October 2023 to 32 crashes in October 2024. Crashes attributed to 'Followed too closely' increased by 4, from 14 to 18, and 'Failed to yield right of way' increased by 6, from 5 to 11. Conversely, 'Inattention' related crashes decreased from 15 to 12, and 'Visibility obstructed' crashes decreased from 5 to 1.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring on 'Wet' road surfaces decreased significantly, from 14 in October 2023 to 5 in October 2024. Correspondingly, crashes during 'Rain' conditions also decreased from 9 to 1. Crashes in 'Daylight' increased from 69 to 74, while crashes during 'Dawn' decreased from 6 to 3 year-over-year.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Road surface condition field
Vehicles & Demographics
Toyota remained the most frequently involved vehicle make, with its count increasing from 30 to 32. Ford saw a significant rise in involvement from 16 vehicles in October 2023 to 31 in October 2024, moving it to the second rank. In terms of persons involved, the 35-44 age group saw a notable increase from 34 to 51, while involvement in the 45-54 age group decreased from 32 to 18.
Top Vehicle Makes (212 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Vehicle unit records
20 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (206 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones decreased from 44 in October 2023 to 31 in October 2024. Conversely, crashes in 35 mph zones increased from 17 to 23, and crashes in 55 mph zones increased from 9 to 15. No fatalities were recorded in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · 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: 2024-10-01 through 2024-10-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-10-01 through 2024-10-31 (31 days)
- Geographic scope: WOBURN, MA
- Total crash records analyzed: 101
- Total persons involved: 231
- Total vehicles involved: 212
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: October 2024." Published June 21, 2026. Reporting period: 2024-10-01 to 2024-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/woburn/october-2024-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: 2024-10-01 – 2024-10-31
Generated: June 21, 2026 · All rights reserved