Monthly Traffic Safety Analysis

34 CRASHES IN
NORWOOD, MA
DECEMBER 2023

All metrics benchmarked againstDecember 2022

In December 2023, NORWOOD experienced 34 crashes, an increase from the 25 crashes recorded in December 2022, representing a 36% rise. Concurrently, total injuries increased from 6 to 10, a 66.7% increase year-over-year. A notable shift is the emergence of 1 serious injury crash in the current period, whereas none were reported in the prior year.

34

36.0%was 25

Total Crash Events

0

Persons Killed

10

66.7%was 6

Persons Injured

0

-100.0%was 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 · 2023-12-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for NORWOOD in December shows an upward trend year-over-year, with total crashes increasing by 36% from 25 in December 2022 to 34 in December 2023. This rise in crash incidents was accompanied by a 66.7% increase in total injuries, climbing from 6 to 10.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

10

Motorists Injured

Prior: 666.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes in December shifted year-over-year, with the peak crash day moving from Saturday in 2022 (7 crashes) to Wednesday in 2023 (7 crashes). The peak crash hour also changed, occurring at 1 PM with 6 crashes in 2023, compared to 6 PM with 4 crashes in 2022. Notably, crashes on Thursdays increased significantly from 0 in December 2022 to 5 in December 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero for both December 2022 and December 2023. However, the severity distribution of injury crashes changed, with 1 serious injury crash reported in December 2023, a category that was absent in December 2022. Minor injury crashes increased from 4 to 5, while possible injury crashes doubled from 1 to 2 year-over-year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.9%
Minor Injury5minor injury crashes14.7%
25.0%prior 4
Possible Injury2possible injury crashes5.9%
100.0%prior 1
No Injury26no injury crashes76.5%
30.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'No improper driving' increased from 4 crashes in December 2022 to 6 crashes in December 2023, while 'Followed too closely' decreased from 5 to 4 crashes. 'Disregarded traffic signs, signals, road markings' emerged as a significant factor in December 2023 with 4 crashes, having not been a top factor in the prior year. Additionally, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased from 1 to 3 crashes, and 'Inattention' decreased from 4 to 2 crashes.

Officer-Reported Primary Contributing Cause

No improper driving6 (17.6%)
Followed too closely4 (11.8%)-20.0%prior 5
Disregarded traffic signs, signals, road markings4 (11.8%)
Failed to yield right of way4 (11.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (8.8%)
Other improper action2 (5.9%)
Visibility obstructed2 (5.9%)
Inattention2 (5.9%)
Made an improper turn1 (2.9%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In December 2023, crashes under 'Daylight' conditions significantly increased to 20, compared to 8 in December 2022, while crashes in 'Dark - roadway not lighted' conditions decreased from 5 to 1. The number of crashes on 'Wet' road surfaces doubled from 5 in December 2022 to 10 in December 2023. 'Clear' weather conditions remained the most common for crashes, increasing from 15 to 21 incidents year-over-year.

Weather

Clear21 (61.8%)
40.0%prior 15
Rain4 (11.8%)
Clear/Unknown2 (5.9%)
Cloudy/Rain2 (5.9%)
Clear/Other2 (5.9%)
Fog, smog, smoke1 (2.9%)
Cloudy1 (2.9%)
Rain/Cloudy1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight20 (58.8%)
150.0%prior 8
Dark - lighted roadway11 (32.4%)
22.2%prior 9
Dark - roadway not lighted1 (2.9%)
-80.0%prior 5
Dawn1 (2.9%)
Dusk1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry24 (70.6%)
26.3%prior 19
Wet10 (29.4%)
100.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (63 vehicles)

1
TOYOTA21 (33.3%)
133.3%prior 9
2
HONDA5 (7.9%)
3
FORD5 (7.9%)
0.0%prior 5
4
CHEVROLET4 (6.3%)
5
SUBARU4 (6.3%)
6
LEXUS3 (4.8%)
7
JEEP3 (4.8%)
8
GMC2 (3.2%)
9
VOLVO2 (3.2%)
10
BMW2 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (76 persons with recorded sex)

Male42 (55.3%)
61.5%prior 26
Female34 (44.7%)
41.7%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones increased from 12 in December 2022 to 18 in December 2023, marking a rise of 6 incidents. Crashes in 45 mph zones also saw a notable increase, from 2 to 7 incidents year-over-year. Conversely, crashes in 65 mph zones decreased from 6 to 2, indicating a shift away from higher speed limit roadways for crash occurrences. No fatal crashes were recorded in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · 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: 2023-12-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-12-01 through 2023-12-31 (31 days)
  • Geographic scope: NORWOOD, MA
  • Total crash records analyzed: 34
  • Total persons involved: 79
  • Total vehicles involved: 63

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 2023." Published June 21, 2026. Reporting period: 2023-12-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/norwood/december-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

Norwood, MA Crash Report — December 2023 | ThatCarHitMe.com