Monthly Traffic Safety Analysis

141 CRASHES IN
CAMBRIDGE, MA
SEPTEMBER 2022

All metrics benchmarked againstSeptember 2021

In September 2022, CAMBRIDGE experienced 141 crashes, an 18.5% increase compared to the 119 crashes reported in September 2021. Total injuries also rose from 23 to 31, marking a 34.8% increase year-over-year. The most notable shift was the significant rise in 'Sideswipe, same direction' crashes, which more than doubled from 22 to 51.

141

18.5%was 119

Total Crash Events

0

Persons Killed

31

34.8%was 23

Persons Injured

49

14.0%was 43

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash data for CAMBRIDGE shows an upward trend year-over-year, with total crashes increasing by 18.5% from 119 in September 2021 to 141 in September 2022. This rise in incidents was accompanied by a 34.8% increase in total injuries, going from 23 to 31. Fatalities remained at zero for both periods.

49

Hit-and-Run Crashes — September 2022

14.0% vs prior (43)

The number of hit-and-run crashes increased by 6, from 43 in September 2021 to 49 in September 2022. Despite this increase in count, the hit-and-run rate decreased slightly from 36.1% of all crashes to 34.8%.

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: 1200.0%

5

Cyclists Injured

Prior: 2150.0%

21

Motorists Injured

Prior: 1910.5%

2

Other Injured

Prior: 1100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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 Wednesday (27 crashes) in September 2021 to Thursday (29 crashes) in September 2022. The peak hour for crashes also changed, moving from 5 PM (9 crashes) in the prior period to 2 PM (14 crashes) in the current period. Notably, crashes on Tuesdays saw a significant increase from 8 to 23 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either September 2021 or September 2022. While serious injuries decreased from 2 to 1, minor injuries increased from 12 to 16, and possible injuries rose from 7 to 10. The proportion of crashes involving any injury slightly increased from 17.6% in the prior period to 19.1% in the current period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes0.7%
-50.0%prior 2
Minor Injury16minor injury crashes11.3%
33.3%prior 12
Possible Injury10possible injury crashes7.1%
42.9%prior 7
No Injury81no injury crashes57.4%
12.5%prior 72

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw increases in crash counts year-over-year. 'Disregarded traffic signs, signals, road markings' increased by 5 crashes, from 4 to 9, while 'Inattention' rose by 4 crashes, from 5 to 9. Conversely, 'Failed to yield right of way' crashes decreased by 3, from 6 to 3.

Officer-Reported Primary Contributing Cause

No improper driving33 (23.4%)3.1%prior 32
Inattention9 (6.4%)80.0%prior 5
Disregarded traffic signs, signals, road markings9 (6.4%)
Followed too closely7 (5%)
Other improper action6 (4.3%)
Made an improper turn4 (2.8%)-20.0%prior 5
Failed to yield right of way3 (2.1%)-50.0%prior 6
Over-correcting/over-steering3 (2.1%)
Distracted1 (0.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in Daylight conditions increased significantly from 66 in September 2021 to 103 in September 2022, representing a larger share of incidents. Conversely, crashes in 'Dark - lighted roadway' conditions decreased from 31 to 21. The number of crashes on Dry road surfaces increased by 24, from 83 to 107, while crashes on Wet surfaces remained stable at 18.

Weather

Clear86 (65.2%)
50.9%prior 57
Cloudy11 (8.3%)
37.5%prior 8
Rain11 (8.3%)
0.0%prior 11
Unknown/Unknown6 (4.5%)
Clear/Clear6 (4.5%)
-53.8%prior 13
Cloudy/Cloudy3 (2.3%)
Rain/Cloudy3 (2.3%)
Cloudy/Rain2 (1.5%)
-60.0%prior 5
Cloudy/Unknown1 (0.8%)
Rain/Other1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Weather condition at time of crash

Lighting

Daylight103 (79.2%)
56.1%prior 66
Dark - lighted roadway21 (16.2%)
-32.3%prior 31
Dusk4 (3.1%)
-42.9%prior 7
Dark - roadway not lighted1 (0.8%)
Dark - unknown roadway lighting1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Lighting condition field

Road Surface

Dry107 (84.9%)
28.9%prior 83
Wet18 (14.3%)
0.0%prior 18
Sand, mud, dirt, oil, gravel1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Road surface condition field

Vehicles & Demographics

The age group '26-34' saw the largest increase in persons involved in crashes, rising by 20 from 44 to 64. The number of female persons involved in crashes increased by 24, from 67 to 91. Among vehicle makes, FORD saw a significant increase of 16 crashes, from 19 to 35, while TOYOTA remained the most common make despite a slight decrease in count.

Top Vehicle Makes (256 vehicles)

1
TOYOTA45 (17.6%)
-4.3%prior 47
2
FORD35 (13.7%)
84.2%prior 19
3
HONDA21 (8.2%)
-22.2%prior 27
4
NISSAN19 (7.4%)
90.0%prior 10
5
CHEVROLET12 (4.7%)
140.0%prior 5
6
SUBARU10 (3.9%)
-28.6%prior 14
7
BMW7 (2.7%)
8
KIA6 (2.3%)
9
RAM6 (2.3%)
10
FRHT5 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Vehicle unit records

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

Sex Distribution (212 persons with recorded sex)

Male119 (56.1%)
0.8%prior 118
Female91 (42.9%)
35.8%prior 67
R2 (0.9%)
100.0%prior 1

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Person-level records linked to crash events

Speed Limit Zones

The majority of crashes in both periods occurred in the 25 MPH speed limit zone, which saw an increase of 29 crashes from 71 to 100. Crashes in the 20 MPH, 30 MPH, and 35 MPH speed limit zones each saw slight decreases year-over-year. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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: 2022-09-01 through 2022-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-09-01 through 2022-09-30 (30 days)
  • Geographic scope: CAMBRIDGE, MA
  • Total crash records analyzed: 141
  • Total persons involved: 296
  • 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: September 2022." Published June 21, 2026. Reporting period: 2022-09-01 to 2022-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/cambridge/september-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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Cambridge, MA Crash Report — September 2022 | ThatCarHitMe.com