Monthly Traffic Safety Analysis

37 CRASHES IN
BURLINGTON, MA
JULY 2022

All metrics benchmarked againstJuly 2021

Total crashes decreased by 22.9%, from 48 crashes in July 2021 to 37 crashes in July 2022. The most notable shift was the decrease in wet road surface crashes, which dropped from 15 to 1. Overall, fatalities remained at zero for both periods.

37

▼ -22.9%was 48

Total Crash Events

0

Persons Killed

17

▼ -15.0%was 20

Persons Injured

1

▼ -50.0%was 2

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 · 2022-07-01 to 2022-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for July 2022 indicates a downward trend compared to July 2021. Total crashes decreased by 22.9%, from 48 to 37. Similarly, total injuries decreased from 20 to 17.

1

Hit-and-Run Crashes — July 2022

▼ -50.0% vs prior (2)

Hit-and-run crashes decreased from 2 in July 2021 to 1 in July 2022. Consequently, the hit-and-run crash rate decreased from 4.2% to 2.7% year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

17

Motorists Injured

Prior: 20↓-15.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · 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 Friday with 10 crashes in July 2021 to Wednesday with 10 crashes in July 2022. The peak hour also shifted, with July 2021 seeing 5 crashes at 3 p.m., while July 2022 recorded 7 crashes at 5 p.m.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero for both periods. Total injuries decreased from 20 in July 2021 to 17 in July 2022. While serious injuries remained at 1 and minor injuries remained at 10 in both periods, possible injuries decreased from 5 to 2.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.7%
→0.0%prior 1
Minor Injury10minor injury crashes27%
→0.0%prior 10
Possible Injury2possible injury crashes5.4%
↓-60.0%prior 5
No Injury24no injury crashes64.9%
↓-25.0%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "Followed too closely" decreased from 8 to 7, and "Inattention" decreased from 7 to 4 crashes. Conversely, crashes with "No improper driving" as a factor increased from 3 to 7. "Exceeded authorized speed limit" increased from 2 to 3 crashes, while "Driving too fast for conditions" decreased from 4 to 1 crash.

Officer-Reported Primary Contributing Cause

Followed too closely7 (18.9%)↓-12.5%prior 8
No improper driving7 (18.9%)
Inattention4 (10.8%)↓-42.9%prior 7
Failed to yield right of way4 (10.8%)↓-20.0%prior 5
Exceeded authorized speed limit3 (8.1%)
Other improper action1 (2.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.7%)
Visibility obstructed1 (2.7%)
Wrong side or wrong way1 (2.7%)
Distracted1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The number of crashes occurring in clear weather conditions increased from 27 to 32. Crashes on wet road surfaces saw a significant decrease, falling from 15 in July 2021 to 1 in July 2022. Crashes occurring in dark-lighted roadway conditions decreased from 8 to 0.

Weather

Clear32 (88.9%)
↑18.5%prior 27
Cloudy2 (5.6%)
↓-66.7%prior 6
Clear/Cloudy1 (2.8%)
Cloudy/Rain1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Weather condition at time of crash

Lighting

Daylight36 (97.3%)
↓-2.7%prior 37
Dark - roadway not lighted1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Lighting condition field

Road Surface

Dry35 (97.2%)
↑6.1%prior 33
Wet1 (2.8%)
↓-93.3%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 93 in July 2021 to 72 in July 2022. HONDA and TOYOTA involvement both decreased, from 17 to 12 and 17 to 10, respectively. The 16-20 age group saw a decrease in representation from 13 to 5 persons, while the 65+ age group increased from 9 to 14 persons.

Top Vehicle Makes (72 vehicles)

1
HONDA12 (16.7%)
↓-29.4%prior 17
2
TOYOTA10 (13.9%)
↓-41.2%prior 17
3
FORD6 (8.3%)
4
CHEVROLET6 (8.3%)
↓-14.3%prior 7
5
ACURA3 (4.2%)
6
HD3 (4.2%)
7
JEEP3 (4.2%)
↓-40.0%prior 5
8
MERCEDES-BENZ3 (4.2%)
9
SUBARU3 (4.2%)
10
MAZDA2 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Vehicle unit records

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

Sex Distribution (84 persons with recorded sex)

Male49 (58.3%)
↓-18.3%prior 60
Female35 (41.7%)
↓-20.5%prior 44

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 35 mph speed zones slightly decreased from 16 to 15. A more substantial decrease was observed in 55 mph zones, which dropped from 15 crashes to 8. Crashes in 30 mph zones also decreased from 10 to 5. No fatalities were reported in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · 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: 2022-07-01 through 2022-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-07-01 through 2022-07-31 (31 days)
  • Geographic scope: BURLINGTON, MA
  • Total crash records analyzed: 37
  • Total persons involved: 91
  • Total vehicles involved: 72

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). "BURLINGTON, MA Crash Intelligence Report: July 2022." Published June 21, 2026. Reporting period: 2022-07-01 to 2022-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/burlington/july-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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Burlington, MA Crash Report — July 2022 | ThatCarHitMe.com