Monthly Traffic Safety Analysis

142 CRASHES IN
CAMBRIDGE, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

Total crashes in Cambridge increased by 71.08% from 83 in December 2023 to 142 in December 2024. The most notable year-over-year shift was a 300% increase in total injuries, rising from 9 to 36. Fatalities remained at 0 in both periods.

142

71.1%was 83

Total Crash Events

0

Persons Killed

36

300.0%was 9

Persons Injured

46

53.3%was 30

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

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, crashes in December 2024 increased significantly compared to December 2023, rising from 83 crashes to 142 crashes, a 71.08% increase. Concurrently, total injuries also saw a substantial increase, rising from 9 to 36, representing a 300% surge year-over-year. Fatalities remained at 0 in both periods.

46

Hit-and-Run Crashes — December 2024

53.3% vs prior (30)

The number of hit-and-run crashes increased from 30 in December 2023 to 46 in December 2024. Despite this increase in count, the hit-and-run rate decreased slightly from 36.1% of total crashes in December 2023 to 32.4% in December 2024. This indicates that while the absolute number of hit-and-run incidents rose, their proportion relative to all crashes decreased.

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%

4

Pedestrians Injured

Prior: 333.3%

4

Cyclists Injured

Prior: 1300.0%

27

Motorists Injured

Prior: 5440.0%

1

Other Injured

Prior: 0%

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

In December 2024, Friday remained the peak day for crashes with 31 incidents, up from 17 on Fridays in December 2023. The peak hour shifted from 2 PM with 10 crashes in December 2023 to 1 PM with 14 crashes in December 2024. While both periods saw the highest crash frequency towards the end of the work week and in the afternoon, the overall number of incidents increased across most days and hours.

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

Total injuries significantly increased from 9 in December 2023 to 36 in December 2024. No fatal crashes were recorded in either period. The number of serious injuries (A) rose from 0 to 1, minor injuries (B) increased from 5 to 17, and possible injuries (C) increased from 2 to 11.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes0.7%
Minor Injury17minor injury crashes12%
240.0%prior 5
Possible Injury11possible injury crashes7.7%
450.0%prior 2
No Injury82no injury crashes57.7%
51.9%prior 54

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

The contributing factor 'No improper driving' increased from 22 counts in December 2023 to 32 counts in December 2024. 'Other improper action' saw a notable increase from 3 counts to 10 counts, and 'Followed too closely' rose from 1 count to 9 counts. 'Failed to yield right of way' also increased slightly from 8 counts to 9 counts year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving32 (22.5%)45.5%prior 22
Other improper action10 (7%)
Failed to yield right of way9 (6.3%)12.5%prior 8
Followed too closely9 (6.3%)
Inattention7 (4.9%)
Visibility obstructed3 (2.1%)
Glare2 (1.4%)
Driving too fast for conditions2 (1.4%)
Failure to keep in proper lane or running off road2 (1.4%)
Disregarded traffic signs, signals, road markings2 (1.4%)-66.7%prior 6

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 'Clear' weather conditions increased from 41 in December 2023 to 69 in December 2024. Incidents during 'Daylight' conditions rose from 47 to 80, and those on 'Dry' road surfaces increased from 54 to 93. While the proportional distribution across conditions remained broadly similar, the absolute number of crashes increased in all major categories.

Weather

Clear69 (51.1%)
68.3%prior 41
Clear/Clear21 (15.6%)
250.0%prior 6
Cloudy10 (7.4%)
66.7%prior 6
Snow8 (5.9%)
Rain7 (5.2%)
-46.2%prior 13
Cloudy/Cloudy3 (2.2%)
Unknown/Unknown2 (1.5%)
Rain/Rain2 (1.5%)
Rain/Fog, smog, smoke1 (0.7%)
Rain/Other1 (0.7%)

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

Lighting

Daylight80 (61.1%)
70.2%prior 47
Dark - lighted roadway44 (33.6%)
91.3%prior 23
Dawn2 (1.5%)
Dark - roadway not lighted2 (1.5%)
Dusk2 (1.5%)
Dark - unknown roadway lighting1 (0.8%)

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

Road Surface

Dry93 (69.4%)
72.2%prior 54
Wet27 (20.1%)
42.1%prior 19
Snow10 (7.5%)
Slush3 (2.2%)
Ice1 (0.7%)

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

Vehicles & Demographics

Toyota became the top vehicle make involved in crashes in December 2024 with 47 incidents, surpassing Honda which had 33 incidents. In December 2023, Honda was the top make with 23 incidents, followed by Toyota with 20. The 26-34 age group continued to represent the highest number of persons involved in crashes, increasing from 23 in December 2023 to 54 in December 2024.

Top Vehicle Makes (256 vehicles)

1
TOYOTA47 (18.4%)
135.0%prior 20
2
HONDA33 (12.9%)
43.5%prior 23
3
FORD29 (11.3%)
81.3%prior 16
4
CHEVROLET12 (4.7%)
5
SUBARU12 (4.7%)
100.0%prior 6
6
MAZDA10 (3.9%)
7
VOLKSWAGEN9 (3.5%)
12.5%prior 8
8
NISSAN9 (3.5%)
-18.2%prior 11
9
BMW8 (3.1%)
10
HYUNDAI7 (2.7%)
0.0%prior 7

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

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

Sex Distribution (225 persons with recorded sex)

Male133 (59.1%)
98.5%prior 67
Female92 (40.9%)
95.7%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 25 mph speed zones increased from 60 in December 2023 to 93 in December 2024. Similarly, crashes in 20 mph zones rose from 11 to 33, and in 35 mph zones from 7 to 11. No fatal crashes 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: CAMBRIDGE, MA
  • Total crash records analyzed: 142
  • Total persons involved: 306
  • Total vehicles involved: 256

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). "CAMBRIDGE, 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/cambridge/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

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