ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WOBURN, MA · MAY 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/may-2024-report
Monthly Traffic Safety Analysis
88 CRASHES IN
WOBURN, MA
MAY 2024
Total crashes in WOBURN increased by 4.76%, from 84 in May 2023 to 88 in May 2024. During this period, speeding-related crashes saw a significant increase, rising by 200% from 1 crash to 3 crashes.
88
▲ 4.8%was 84
Total Crash Events
0
Persons Killed
24
▼ -17.2%was 29
Persons Injured
10
▲ 25.0%was 8
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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the number of crashes in WOBURN increased by 4.76% year-over-year, from 84 crashes in May 2023 to 88 crashes in May 2024. Despite this increase in total crashes, the number of injuries decreased by 17.24%, falling from 29 to 24. Fatalities remained stable at zero in both periods.
10
Hit-and-Run Crashes — May 2024
▲ 25.0% vs prior (8)
The number of hit-and-run crashes increased from 8 in May 2023 to 10 in May 2024. This represents an increase in the hit-and-run rate from 9.5% of total crashes to 11.4% year-over-year. The trend indicates an upward trajectory for hit-and-run incidents.
Vulnerable Road User Casualties
0
Motorists Killed
24
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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 Friday in May 2023, with 15 crashes, to Thursday in May 2024, with 21 crashes. Similarly, the peak hour for crashes moved from 5 p.m. with 11 crashes in May 2023 to 3 p.m. with 13 crashes in May 2024. These changes suggest a shift in the timing of crash occurrences.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either May 2023 or May 2024. Serious injury crashes increased from 1 (1.2% share) to 2 (2.3% share) year-over-year. Concurrently, minor injury crashes decreased from 11 (13.1% share) to 10 (11.4% share), and possible injury crashes decreased from 12 (14.3% share) to 7 (8% share). The proportion of crashes resulting in no injuries increased from 66.7% to 76.1%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Most severe injury per crash record
Top Contributing Factors
No improper driving remained the most frequent contributing factor, increasing from 21 crashes in May 2023 to 24 crashes in May 2024, a 14.3% increase in count. Failed to yield right of way crashes saw a notable increase of 66.7% in count, rising from 9 to 15 crashes, moving it from the fourth to the second most common factor. Conversely, crashes attributed to Followed too closely decreased by 22.2% in count, from 9 to 7 crashes, and Failure to keep in proper lane or running off road decreased by 20% in count, from 5 to 4 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring in clear weather remained high, with 70 crashes in May 2024 compared to 72 in May 2023. Crashes in cloudy conditions increased from 3 to 6, while rain-related crashes remained stable at 6. Regarding lighting, daylight crashes increased from 63 to 75, and crashes in dark-lighted roadway conditions rose from 10 to 11. The number of crashes on wet road surfaces increased by 83.3%, from 6 in May 2023 to 11 in May 2024, while crashes on dry surfaces remained constant at 77.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes remained Toyota and Honda, with Toyota increasing from 28 to 40 and Honda from 23 to 27. Chevrolet and Jeep also saw increases in involvement, with Chevrolet rising from 9 to 15 and Jeep from 6 to 10. Regarding age distribution, there was a decrease in persons aged 0-15 (from 13 to 6), 16-20 (from 25 to 12), 26-34 (from 44 to 31), and 55-64 (from 24 to 18). Conversely, increases were observed in the 21-25 age group (from 12 to 19), 45-54 age group (from 26 to 30), and 65+ age group (from 19 to 26).
Top Vehicle Makes (181 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Vehicle unit records
19 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (169 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph zones increased from 23 in May 2023 to 30 in May 2024, and crashes in 35 mph zones rose from 20 to 24. Conversely, crashes in higher speed zones decreased, with 55 mph zones seeing a drop from 11 to 9 crashes, and 65 mph zones experiencing a decrease from 14 to 7 crashes. There were no fatal crashes reported in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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: 2024-05-01 through 2024-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-05-01 through 2024-05-31 (31 days)
- Geographic scope: WOBURN, MA
- Total crash records analyzed: 88
- Total persons involved: 198
- Total vehicles involved: 181
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: May 2024." Published June 21, 2026. Reporting period: 2024-05-01 to 2024-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/woburn/may-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: 2024-05-01 – 2024-05-31
Generated: June 21, 2026 · All rights reserved