Monthly Traffic Safety Analysis

25 CRASHES IN
NORWOOD, MA
DECEMBER 2022

All metrics benchmarked againstDecember 2021

NORWOOD experienced a notable decrease in crash activity in December 2022 compared to December 2021. Total crashes fell by 35.9%, from 39 crashes in the prior period to 25 crashes in the current period. This reduction was accompanied by a 53.8% decrease in total injuries, which dropped from 13 to 6.

25

-35.9%was 39

Total Crash Events

0

Persons Killed

6

-53.8%was 13

Persons Injured

1

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in NORWOOD showed a significant downward trend year-over-year, with total crashes decreasing by 14 incidents, representing a 35.9% reduction from the prior period.

1

Hit-and-Run Crashes — December 2022

4.0% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

6

Motorists Injured

Prior: 11-45.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · 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 with 8 crashes in the prior period to Saturday with 7 crashes in the current period. Similarly, the peak hour for crashes moved from 5 PM with 5 crashes in the prior period to 6 PM with 4 crashes in the current period, indicating a slight shift in daily and weekly crash patterns.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities recorded in either December 2021 or December 2022. Total injuries decreased from 13 in the prior period to 6 in the current period, with minor injuries falling from 7 to 4 and possible injuries from 3 to 1. The proportion of 'No Injury' crashes increased from 74.4% in the prior period to 80% in the current period, despite a decrease in their absolute count from 29 to 20.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes16%
-42.9%prior 7
Possible Injury1possible injury crashes4%
-66.7%prior 3
No Injury20no injury crashes80%
-31.0%prior 29

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Followed too closely' saw an increase in count from 2 crashes in the prior period to 5 crashes in the current period. Conversely, 'No improper driving' decreased from 9 crashes to 4 crashes, 'Failed to yield right of way' decreased from 6 crashes to 3 crashes, and 'Inattention' decreased from 5 crashes to 4 crashes. The top contributing factor shifted from 'No improper driving' in the prior period to 'Followed too closely' in the current period.

Officer-Reported Primary Contributing Cause

Followed too closely5 (20%)
No improper driving4 (16%)-55.6%prior 9
Inattention4 (16%)-20.0%prior 5
Failed to yield right of way3 (12%)-50.0%prior 6
Failure to keep in proper lane or running off road2 (8%)
Over-correcting/over-steering1 (4%)
Distracted1 (4%)
Emotional1 (4%)
History heart/epilepsy/fainting1 (4%)
Made an improper turn1 (4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 32 in the prior period to 15 in the current period, while crashes in rainy conditions increased from 1 to 4. Crashes during daylight hours decreased significantly from 20 to 8, but crashes in 'Dark - roadway not lighted' conditions increased from 1 to 5. Crashes on dry road surfaces decreased from 32 to 19, and crashes on wet road surfaces decreased from 6 to 5.

Weather

Clear15 (62.5%)
-53.1%prior 32
Rain4 (16.7%)
Clear/Unknown1 (4.2%)
Cloudy1 (4.2%)
Cloudy/Rain1 (4.2%)
Snow1 (4.2%)
Clear/Cloudy1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Dark - lighted roadway9 (36.0%)
-40.0%prior 15
Daylight8 (32.0%)
-60.0%prior 20
Dark - roadway not lighted5 (20.0%)
Dusk3 (12.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry19 (76.0%)
-40.6%prior 32
Wet5 (20.0%)
-16.7%prior 6
Snow1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (48 vehicles)

1
TOYOTA9 (18.8%)
-25.0%prior 12
2
FORD5 (10.4%)
-50.0%prior 10
3
HYUNDAI4 (8.3%)
4
JEEP4 (8.3%)
5
CHEVROLET3 (6.3%)
-66.7%prior 9
6
HONDA3 (6.3%)
-76.9%prior 13
7
LEXUS3 (6.3%)
8
NISSAN2 (4.2%)
-66.7%prior 6
9
SUBARU2 (4.2%)
10
GMC2 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (50 persons with recorded sex)

Male26 (52.0%)
-45.8%prior 48
Female24 (48.0%)
-33.3%prior 36

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased from 24 in the prior period to 12 in the current period, and those in 45 mph zones decreased from 6 to 2. In contrast, crashes in 65 mph zones increased from 3 to 6. Speed zones of 25 mph and 50 mph, which had 2 and 1 crash respectively in the prior period, were not present in the current period's crash data, while 5 mph and 15 mph zones each recorded 1 crash in the current period. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · 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: 2022-12-01 through 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-12-01 through 2022-12-31 (31 days)
  • Geographic scope: NORWOOD, MA
  • Total crash records analyzed: 25
  • Total persons involved: 54
  • Total vehicles involved: 48

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: December 2022." Published June 21, 2026. Reporting period: 2022-12-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/norwood/december-2022-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 — December 2022 | ThatCarHitMe.com