Monthly Traffic Safety Analysis

153 CRASHES IN
FRAMINGHAM, MA
DECEMBER 2022

All metrics benchmarked againstDecember 2021

Total crashes in FRAMINGHAM for December 2022 were 153, an increase from 145 crashes in December 2021. This represents a 5.5% year-over-year increase in total crashes. The most notable shift was an 833.3% increase in total injuries, rising from 6 in December 2021 to 56 in December 2022.

153

5.5%was 145

Total Crash Events

0

Persons Killed

56

833.3%was 6

Persons Injured

15

-21.1%was 19

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

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 December 2022 showed an upward trend compared to December 2021, with total crashes increasing by 5.5% from 145 to 153. While total fatalities remained at 0 in both periods, total injuries saw a substantial increase of 833.3%, rising from 6 to 56.

15

Hit-and-Run Crashes — December 2022

-21.1% vs prior (19)

Hit-and-run incidents decreased in December 2022 compared to December 2021. The number of hit-and-run crashes fell from 19 to 15, resulting in a decrease in the hit-and-run rate from 13.1% to 9.8%. This indicates a downward trend in both the count and proportion of hit-and-run crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 0%

1

Cyclists Injured

Prior: 0%

51

Motorists Injured

Prior: 6750.0%

1

Other Injured

Prior: 0%

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 temporal patterns of crashes shifted between the two periods. In December 2022, the peak day for crashes was Friday with 35 incidents, an increase from 25 crashes on Fridays in December 2021. The peak hour for crashes also shifted from 2 PM with 13 crashes in December 2021 to 5 PM with 16 crashes in December 2022.

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

The severity distribution of crashes changed significantly year-over-year, despite no fatalities in either period. Total injuries increased from 6 in December 2021 to 56 in December 2022. Serious injury crashes, which were not explicitly reported in December 2021, accounted for 2 incidents in December 2022, while minor injury crashes increased from 4 to 16, and possible injury crashes rose from 2 to 24.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes1.3%
Minor Injury16minor injury crashes10.5%
300.0%prior 4
Possible Injury24possible injury crashes15.7%
1100.0%prior 2
No Injury105no injury crashes68.6%
208.8%prior 34

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

Several contributing factors showed notable changes year-over-year. Crashes attributed to "Disregarded traffic signs, signals, road markings" increased by 80%, from 5 incidents in December 2021 to 9 in December 2022. "Inattention" related crashes increased by 50%, from 4 to 6, and "Driving too fast for conditions" also increased by 50%, from 4 to 6 incidents. The "Distracted" factor, which accounted for 8 crashes in December 2021, was not present in the top contributing factors for December 2022.

Officer-Reported Primary Contributing Cause

No improper driving39 (25.5%)8.3%prior 36
Followed too closely23 (15%)4.5%prior 22
Failed to yield right of way15 (9.8%)-16.7%prior 18
Failure to keep in proper lane or running off road10 (6.5%)0.0%prior 10
Disregarded traffic signs, signals, road markings9 (5.9%)80.0%prior 5
Inattention6 (3.9%)
Driving too fast for conditions6 (3.9%)
Other improper action4 (2.6%)-33.3%prior 6
Exceeded authorized speed limit2 (1.3%)
Made an improper turn2 (1.3%)

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

Adverse weather conditions contributed to a higher number of crashes in December 2022 compared to the prior year. Crashes during rain conditions (Rain + Rain/Rain) increased from 8 to 28, and snow conditions increased from 3 to 9. Conversely, crashes during clear weather (Clear + Clear/Clear) decreased from 105 to 88. The number of crashes on wet road surfaces increased from 27 to 37, and on snow-covered surfaces from 2 to 8.

Weather

Clear/Clear48 (31.4%)
2.1%prior 47
Clear40 (26.1%)
-31.0%prior 58
Rain14 (9.2%)
180.0%prior 5
Rain/Rain14 (9.2%)
Cloudy/Cloudy12 (7.8%)
Cloudy8 (5.2%)
-38.5%prior 13
Rain/Cloudy4 (2.6%)
Snow3 (2.0%)
Snow/Sleet, hail (freezing rain or drizzle)2 (1.3%)
Snow/Cloudy2 (1.3%)

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

Lighting

Daylight78 (51.7%)
-2.5%prior 80
Dark - lighted roadway55 (36.4%)
0.0%prior 55
Dark - roadway not lighted9 (6.0%)
50.0%prior 6
Dawn4 (2.6%)
Dusk4 (2.6%)
Dark - unknown roadway lighting1 (0.7%)

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

Road Surface

Dry104 (68.4%)
-6.3%prior 111
Wet37 (24.3%)
37.0%prior 27
Snow8 (5.3%)
Ice3 (2.0%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 280 in December 2021 to 298 in December 2022. Toyota vehicles involved in crashes increased by 20, from 36 to 56, while Honda vehicles remained constant at 45. The age group 0-15 saw a substantial increase in persons involved, rising from 15 to 34, while the 26-34 age group decreased from 79 to 65. The number of females involved in crashes increased from 122 to 169, while males decreased from 197 to 184.

Top Vehicle Makes (298 vehicles)

1
TOYOTA56 (18.8%)
55.6%prior 36
2
HONDA45 (15.1%)
0.0%prior 45
3
FORD30 (10.1%)
-6.3%prior 32
4
CHEVROLET20 (6.7%)
53.8%prior 13
5
NISSAN19 (6.4%)
26.7%prior 15
6
JEEP14 (4.7%)
55.6%prior 9
7
KIA9 (3%)
8
HYUNDAI9 (3%)
-10.0%prior 10
9
BMW8 (2.7%)
14.3%prior 7
10
MAZDA8 (2.7%)
0.0%prior 8

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

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

Sex Distribution (353 persons with recorded sex)

Male184 (52.1%)
-6.6%prior 197
Female169 (47.9%)
38.5%prior 122

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

The distribution of crashes across speed zones saw shifts year-over-year, with no fatal crashes reported in any speed zone during either period. Crashes in 25 mph zones increased from 6 to 10, while crashes in 30 mph zones decreased from 13 to 4. Crashes in 65 mph zones slightly decreased from 17 to 15.

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: FRAMINGHAM, MA
  • Total crash records analyzed: 153
  • Total persons involved: 392
  • Total vehicles involved: 298

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). "FRAMINGHAM, 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/framingham/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

ThatCarHitMe.com · An Injuria.ai Company

Framingham, MA Crash Report — December 2022 | ThatCarHitMe.com