Monthly Traffic Safety Analysis

68 CRASHES IN
WESTWOOD, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

In December 2024, WESTWOOD experienced 68 total crashes, an increase from 53 crashes in December 2023, representing a 28.3% rise. Total injuries also saw a significant increase, rising by 85.7% from 7 in the prior period to 13 in the current period. There were no fatalities reported in either period.

68

28.3%was 53

Total Crash Events

0

Persons Killed

13

85.7%was 7

Persons Injured

3

-40.0%was 5

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 · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for WESTWOOD indicates an upward trend year-over-year, with total crashes increasing by 28.3% from 53 to 68. This rise was accompanied by an 85.7% increase in total injuries, from 7 to 13, while fatalities remained at zero in both periods.

3

Hit-and-Run Crashes — December 2024

-40.0% vs prior (5)

Hit-and-run crashes decreased from 5 in December 2023 to 3 in December 2024. Consequently, the hit-and-run rate decreased from 9.4% in the prior period to 4.4% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

13

Motorists Injured

Prior: 785.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted year-over-year, with the peak day moving from Monday in December 2023 (11 crashes) to Friday in December 2024 (23 crashes). The peak hour also shifted, from 1 PM (6 crashes) in the prior period to 2 PM (9 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero for both periods, indicating no change in the fatal crash rate. However, the number of serious injuries increased from 0 in December 2023 to 1 in December 2024, and minor injuries rose from 1 (1.9% of crashes) to 4 (5.9% of crashes).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.5%
Minor Injury4minor injury crashes5.9%
300.0%prior 1
Possible Injury6possible injury crashes8.8%
20.0%prior 5
No Injury57no injury crashes83.8%
23.9%prior 46

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Followed too closely' increased in count from 8 crashes in the prior period to 14 crashes in the current period. 'No improper driving' also saw an increase, from 6 crashes to 12 crashes, and 'Failed to yield right of way' rose from 6 crashes to 9 crashes. 'Driving too fast for conditions' increased from 2 crashes to 6 crashes, while 'Inattention' decreased from 5 crashes to 4 crashes.

Officer-Reported Primary Contributing Cause

Followed too closely14 (20.6%)75.0%prior 8
No improper driving12 (17.6%)100.0%prior 6
Failed to yield right of way9 (13.2%)50.0%prior 6
Driving too fast for conditions6 (8.8%)
Failure to keep in proper lane or running off road6 (8.8%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway5 (7.4%)
Inattention4 (5.9%)-20.0%prior 5
Other improper action3 (4.4%)
Illness2 (2.9%)
Exceeded authorized speed limit1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in snowy weather conditions significantly increased, with 'Snow/Snow' conditions accounting for 10 crashes in the current period compared to 0 in the prior period. Correspondingly, crashes on 'Snow' road surfaces rose from 0 to 16. Crashes in 'Daylight' conditions also increased from 31 to 44.

Weather

Clear/Clear18 (26.5%)
-21.7%prior 23
Clear15 (22.1%)
25.0%prior 12
Snow/Snow10 (14.7%)
Rain/Rain5 (7.4%)
Snow5 (7.4%)
Cloudy/Cloudy4 (5.9%)
Rain3 (4.4%)
-50.0%prior 6
Cloudy2 (2.9%)
Rain/Cloudy2 (2.9%)
Sleet, hail (freezing rain or drizzle)/Snow1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight44 (64.7%)
41.9%prior 31
Dark - lighted roadway17 (25.0%)
6.3%prior 16
Dark - roadway not lighted6 (8.8%)
Other1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry34 (50.0%)
-15.0%prior 40
Wet17 (25.0%)
41.7%prior 12
Snow16 (23.5%)
Ice1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

Toyota remained the top vehicle make involved in crashes with 18 vehicles in both periods. Honda increased from 14 to 17 vehicles, and Ford saw a notable rise from 7 to 14 vehicles. The 26-34 age group experienced a substantial increase in person count from 16 to 33, while the 65+ age group also saw an increase from 11 to 19.

Top Vehicle Makes (125 vehicles)

1
TOYOTA18 (14.4%)
0.0%prior 18
2
HONDA17 (13.6%)
21.4%prior 14
3
FORD14 (11.2%)
100.0%prior 7
4
CHEVROLET12 (9.6%)
33.3%prior 9
5
JEEP10 (8%)
6
HYUNDAI6 (4.8%)
7
NISSAN6 (4.8%)
8
MERCEDES-BENZ5 (4%)
9
BMW5 (4%)
10
VOLKSWAGEN4 (3.2%)
-33.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (144 persons with recorded sex)

Male77 (53.5%)
32.8%prior 58
Female67 (46.5%)
42.6%prior 47

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone increased from 25 in the prior period to 33 in the current period. Crashes in the 55 mph zone also rose from 6 to 8. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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: 2024-12-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-12-01 through 2024-12-31 (31 days)
  • Geographic scope: WESTWOOD, MA
  • Total crash records analyzed: 68
  • Total persons involved: 155
  • Total vehicles involved: 125

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). "WESTWOOD, MA Crash Intelligence Report: December 2024." Published June 21, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/westwood/december-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

Westwood, MA Crash Report — December 2024 | ThatCarHitMe.com