Monthly Traffic Safety Analysis

17 CRASHES IN
BEDFORD, MA
DECEMBER 2022

All metrics benchmarked againstDecember 2021

BEDFORD experienced a 21.4% increase in total crashes, rising from 14 in December 2021 to 17 in December 2022. Despite this increase in crash events, the total number of injuries remained stable at 2 in both periods, and no fatalities were recorded. The most notable shift was the 100% increase in crashes attributed to 'Failed to yield right of way,' which became the leading contributing factor in the current period.

17

21.4%was 14

Total Crash Events

0

Persons Killed

2

Persons Injured

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 · 2022-12-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in BEDFORD increased by 21.4% year-over-year, with 17 crashes reported in December 2022 compared to 14 in December 2021. This represents an increase of 3 crash events. The total number of injuries remained stable at 2 in both periods.

1

Hit-and-Run Crashes — December 2022

5.9% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 20.0%

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 peak day for crashes shifted from Tuesday in December 2021 (4 crashes) to Friday in December 2022 (4 crashes). The peak hour remained 4 p.m. in both periods, but the number of crashes at this hour doubled from 3 in December 2021 to 6 in December 2022. Additionally, crashes on Sundays increased from 1 to 3, and Tuesdays saw a decrease from 4 crashes to 0.

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

Fatalities remained at 0 in both December 2021 and December 2022. The total number of injuries also remained constant at 2 across both periods. In December 2021, both injuries were classified as Minor Injury (14.3% of crashes), while in December 2022, there was 1 Minor Injury (5.9% of crashes) and 1 Possible Injury (5.9% of crashes).

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes5.9%
-50.0%prior 2
Possible Injury1possible injury crashes5.9%
No Injury15no injury crashes88.2%
25.0%prior 12

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

The leading contributing factor shifted significantly, with 'Failed to yield right of way' increasing by 100%, from 3 crashes in December 2021 to 6 crashes in December 2022. Conversely, crashes attributed to 'No improper driving' decreased by 60%, from 5 to 2. 'Followed too closely' crashes also decreased by 50%, from 2 to 1.

Officer-Reported Primary Contributing Cause

Failed to yield right of way6 (35.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (11.8%)
No improper driving2 (11.8%)-60.0%prior 5
Followed too closely1 (5.9%)
Inattention1 (5.9%)
Other improper action1 (5.9%)
Disregarded traffic signs, signals, road markings1 (5.9%)
Visibility obstructed1 (5.9%)
Exceeded authorized speed limit1 (5.9%)
Failure to keep in proper lane or running off road1 (5.9%)

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

Crashes occurring in 'Daylight' conditions decreased from 9 in December 2021 to 7 in December 2022, while crashes in 'Dark - lighted roadway' conditions more than doubled, increasing from 4 to 9. Crashes on 'Wet' road surfaces increased by 100%, from 3 to 6. Additionally, 'Snow' as a road surface condition was noted in 2 crashes in December 2022, but not in the prior period.

Weather

Clear6 (35.3%)
-14.3%prior 7
Rain3 (17.6%)
Snow3 (17.6%)
Cloudy2 (11.8%)
Rain/Cloudy2 (11.8%)
Clear/Clear1 (5.9%)

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

Lighting

Dark - lighted roadway9 (52.9%)
Daylight7 (41.2%)
-22.2%prior 9
Dark - roadway not lighted1 (5.9%)

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

Road Surface

Dry9 (52.9%)
12.5%prior 8
Wet6 (35.3%)
Snow2 (11.8%)

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

Vehicles & Demographics

Top Vehicle Makes (30 vehicles)

1
TOYOTA6 (20%)
-33.3%prior 9
2
VOLKSWAGEN4 (13.3%)
3
SUBARU3 (10%)
4
MAZDA3 (10%)
5
NISSAN2 (6.7%)
6
GMC1 (3.3%)
7
HONDA1 (3.3%)
-80.0%prior 5
8
HYUNDAI1 (3.3%)
9
ACURA1 (3.3%)
10
LEXUS1 (3.3%)

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

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

Sex Distribution (39 persons with recorded sex)

Male21 (53.8%)
23.5%prior 17
Female18 (46.2%)
38.5%prior 13

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

Crashes in the 30 mph speed zone increased from 5 in December 2021 to 7 in December 2022. Conversely, crashes in the 35 mph zone decreased from 3 to 1, and in the 40 mph zone, they decreased from 4 to 3. New crash occurrences were noted in the 20 mph zone (3 crashes) and the 55 mph zone (1 crash) in December 2022, which had no crashes in the prior period. No fatal crashes were reported in any speed zone during either period.

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: BEDFORD, MA
  • Total crash records analyzed: 17
  • Total persons involved: 40
  • Total vehicles involved: 30

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). "BEDFORD, 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/bedford/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

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