Monthly Traffic Safety Analysis

34 CRASHES IN
NORWOOD, MA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

NORWOOD experienced a notable increase in crash activity from September 2023 to September 2024. Total crashes rose from 24 to 34, marking a 41.67% increase year-over-year. The most significant shift was in total injuries, which surged by 225%, from 4 injuries in September 2023 to 13 injuries in September 2024.

34

41.7%was 24

Total Crash Events

0

Persons Killed

13

225.0%was 4

Persons Injured

0

Fatal Crash Events

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a substantial increase in crash incidents, with total crashes rising by 41.67% from 24 to 34. Concurrently, the number of injured persons saw a sharp increase of 225%, from 4 to 13, suggesting a worsening safety trend for the period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 0%

11

Motorists Injured

Prior: 4175.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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 Saturday in September 2023, with 6 crashes, to Tuesday in September 2024, also with 6 crashes. The peak hour for crashes also changed, moving from 4 PM with 5 crashes in the prior period to 12 PM with 6 crashes in the current period. This indicates a shift in the times and days when crashes are most concentrated.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero for both September 2023 and September 2024. However, the number of crashes resulting in injuries increased significantly, with total injuries rising from 4 to 13. Specifically, serious injuries (code 'A') increased from 0 to 1, and possible injuries (code 'C') increased from 0 to 4, while minor injuries (code 'B') remained at 4.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.9%
Minor Injury4minor injury crashes11.8%
0.0%prior 4
Possible Injury4possible injury crashes11.8%
No Injury25no injury crashes73.5%
31.6%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Inattention' decreased by 40% in count, from 10 crashes in September 2023 to 6 crashes in September 2024. Conversely, 'Failed to yield right of way' crashes doubled, increasing by 100% from 3 to 6 incidents. 'No improper driving' also saw a 150% increase in count, rising from 2 to 5 crashes year-over-year.

Officer-Reported Primary Contributing Cause

Inattention6 (17.6%)-40.0%prior 10
Failed to yield right of way6 (17.6%)
No improper driving5 (14.7%)
Followed too closely3 (8.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (5.9%)
Other improper action2 (5.9%)
Visibility obstructed2 (5.9%)
Disregarded traffic signs, signals, road markings2 (5.9%)
Fatigued/asleep1 (2.9%)
Failure to keep in proper lane or running off road1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions significantly increased from 12 in September 2023 to 26 in September 2024. Similarly, crashes during 'Daylight' conditions rose from 21 to 28. There was a decrease in crashes on 'Wet' road surfaces, falling from 8 to 4 incidents, while crashes on 'Dry' surfaces increased from 16 to 29.

Weather

Clear26 (76.5%)
116.7%prior 12
Cloudy3 (8.8%)
Rain/Cloudy2 (5.9%)
Cloudy/Rain1 (2.9%)
Rain1 (2.9%)
Rain/Other1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash

Lighting

Daylight28 (82.4%)
33.3%prior 21
Dark - lighted roadway5 (14.7%)
Dark - roadway not lighted1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field

Road Surface

Dry29 (85.3%)
81.3%prior 16
Wet4 (11.8%)
-50.0%prior 8
Sand, mud, dirt, oil, gravel1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (60 vehicles)

1
TOYOTA15 (25%)
66.7%prior 9
2
FORD7 (11.7%)
3
HONDA6 (10%)
20.0%prior 5
4
CHEVROLET5 (8.3%)
5
KIA4 (6.7%)
6
SUBARU3 (5%)
7
LEXUS3 (5%)
8
DODGE3 (5%)
9
NISSAN2 (3.3%)
10
INFI2 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records

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

Sex Distribution (80 persons with recorded sex)

Male45 (56.3%)
28.6%prior 35
Female35 (43.8%)
150.0%prior 14

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes within 30 mph speed zones saw a substantial increase, rising from 14 incidents in September 2023 to 24 in September 2024, a 71.4% change. Crashes in 25 mph zones also increased from 1 to 4, a 300% change, while crashes in 45 mph zones remained constant at 3 for both periods. No fatalities were recorded in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-09-01 through 2024-09-30 (30 days)
  • Geographic scope: NORWOOD, MA
  • Total crash records analyzed: 34
  • Total persons involved: 83
  • Total vehicles involved: 60

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). "NORWOOD, MA Crash Intelligence Report: September 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/norwood/september-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

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Norwood, MA Crash Report — September 2024 | ThatCarHitMe.com