Monthly Traffic Safety Analysis

98 CRASHES IN
WOBURN, MA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

In October 2023, WOBURN, MA recorded 98 total crashes, a decrease from 106 crashes in October 2022, representing a 7.55% reduction. Despite the overall decrease in crashes, total injuries increased by 40%, rising from 25 to 35 year-over-year. Hit-and-run incidents also saw a significant increase, rising from 3 to 12 crashes, which is a 300% increase.

98

-7.5%was 106

Total Crash Events

0

Persons Killed

35

40.0%was 25

Persons Injured

12

300.0%was 3

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. 5 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in WOBURN, MA show a slight decrease year-over-year, with total crashes falling by 8 incidents from 106 in October 2022 to 98 in October 2023. However, total injuries increased from 25 to 35, indicating a shift towards more injurious outcomes despite fewer overall crashes. Fatalities remained at zero in both periods.

12

Hit-and-Run Crashes — October 2023

300.0% vs prior (3)

Hit-and-run crashes increased significantly from 3 in October 2022 to 12 in October 2023, representing a 300% increase in count. Consequently, the hit-and-run rate rose from 2.8% of all crashes in October 2022 to 12.2% in October 2023, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 1100.0%

1

Cyclists Injured

Prior: 10.0%

32

Motorists Injured

Prior: 2339.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Wednesday in both periods, with 22 crashes in October 2023 compared to 19 in October 2022. The peak crash hour shifted from 4 p.m. with 13 crashes in October 2022 to 3 p.m. with 10 crashes in October 2023. This indicates a slight change in the specific timing of peak activity within the workday.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes decreased, the number of injuries increased by 40%, from 25 in October 2022 to 35 in October 2023. Serious injuries (Severity A) doubled from 1 to 2, and minor injuries (Severity B) increased by 6, from 11 to 17. The proportion of crashes resulting in no injury decreased from 76.4% to 65.3% year-over-year.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes2%
100.0%prior 1
Minor Injury17minor injury crashes17.3%
54.5%prior 11
Possible Injury10possible injury crashes10.2%
0.0%prior 10
No Injury64no injury crashes65.3%
-21.0%prior 81

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factors 'No improper driving' decreased by 7 crashes (from 30 to 23), 'Inattention' decreased by 3 crashes (from 18 to 15), and 'Followed too closely' decreased by 5 crashes (from 19 to 14). Conversely, 'Visibility obstructed' increased by 4 crashes (from 1 to 5), and 'Distracted' increased by 2 crashes (from 1 to 3). The factor 'Exceeded authorized speed limit' was involved in 2 crashes in October 2023, while it was not listed in October 2022.

Officer-Reported Primary Contributing Cause

No improper driving23 (23.5%)-23.3%prior 30
Inattention15 (15.3%)-16.7%prior 18
Followed too closely14 (14.3%)-26.3%prior 19
Failed to yield right of way5 (5.1%)-37.5%prior 8
Visibility obstructed5 (5.1%)
Failure to keep in proper lane or running off road4 (4.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (3.1%)
Distracted3 (3.1%)
Other improper action3 (3.1%)
Disregarded traffic signs, signals, road markings2 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased slightly from 69 to 72, while crashes in rainy conditions decreased from 13 to 9. A notable shift was observed in road surface conditions, with crashes on wet roads decreasing by 16, from 30 in October 2022 to 14 in October 2023. Crashes in dark-lighted roadway conditions decreased from 24 to 14.

Weather

Clear72 (76.6%)
4.3%prior 69
Rain9 (9.6%)
-30.8%prior 13
Cloudy8 (8.5%)
-11.1%prior 9
Cloudy/Rain2 (2.1%)
-75.0%prior 8
Clear/Unknown1 (1.1%)
Rain/Cloudy1 (1.1%)
Clear/Other1 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash

Lighting

Daylight69 (71.9%)
3.0%prior 67
Dark - lighted roadway14 (14.6%)
-41.7%prior 24
Dawn6 (6.3%)
Dark - roadway not lighted4 (4.2%)
Dusk2 (2.1%)
Dark - unknown roadway lighting1 (1.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field

Road Surface

Dry82 (85.4%)
12.3%prior 73
Wet14 (14.6%)
-53.3%prior 30

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field

Vehicles & Demographics

Among vehicle makes, HONDA and FORD saw decreases in involvement, with HONDA dropping from 33 to 22 and FORD from 27 to 16. TOYOTA also decreased slightly from 32 to 30, while SUBARU involvement increased from 7 to 14. In terms of age distribution, persons aged 21-25 saw a significant decrease in involvement from 37 to 20, while the 65+ age group experienced an increase from 19 to 28.

Top Vehicle Makes (200 vehicles)

1
TOYOTA30 (15%)
-6.3%prior 32
2
HONDA22 (11%)
-33.3%prior 33
3
FORD16 (8%)
-40.7%prior 27
4
SUBARU14 (7%)
100.0%prior 7
5
NISSAN14 (7%)
-22.2%prior 18
6
JEEP11 (5.5%)
-15.4%prior 13
7
CHEVROLET10 (5%)
42.9%prior 7
8
DODGE9 (4.5%)
9
GMC7 (3.5%)
0.0%prior 7
10
HYUNDAI6 (3%)
-40.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records

28 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (186 persons with recorded sex)

Male105 (56.5%)
-11.8%prior 119
Female81 (43.5%)
-12.9%prior 93

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph speed zones increased from 32 in October 2022 to 44 in October 2023, while crashes in 35 mph zones decreased from 26 to 17. Crashes in 55 mph zones also decreased from 14 to 9. No fatal crashes were reported in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-10-01 through 2023-10-31 (31 days)
  • Geographic scope: WOBURN, MA
  • Total crash records analyzed: 98
  • Total persons involved: 221
  • Total vehicles involved: 200

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 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/woburn/october-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

Woburn, MA Crash Report — October 2023 | ThatCarHitMe.com