Monthly Traffic Safety Analysis

21 CRASHES IN
LONGMEADOW, MA
MARCH 2022

All metrics benchmarked againstMarch 2021

In March 2022, LONGMEADOW experienced 21 crashes, an increase of 2 crashes or 10.5% compared to the 19 crashes reported in March 2021. A notable shift includes the rise in hit-and-run crashes, increasing from 0 in March 2021 to 2 in March 2022.

21

10.5%was 19

Total Crash Events

0

Persons Killed

6

20.0%was 5

Persons Injured

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in LONGMEADOW showed an upward trend, with total crashes increasing by 10.5% from 19 in March 2021 to 21 in March 2022. Concurrently, total injuries rose by 20%, from 5 to 6, while fatalities remained at 0 in both periods.

2

Hit-and-Run Crashes — March 2022

9.5% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

5

Motorists Injured

Prior: 50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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 Wednesday, with 5 crashes in March 2021, to Thursday, with 7 crashes in March 2022. The peak hour for crashes remained at 3 incidents but shifted from 7 AM in March 2021 to 8 AM in March 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at 0 in both March 2021 and March 2022. There was an increase in serious injury crashes (severity A), rising from 0 in March 2021 to 1 in March 2022, contributing to an overall increase in total injury crashes from 5 to 6. The proportion of crashes resulting in no injuries decreased from 73.7% in March 2021 to 66.7% in March 2022.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4.8%
Minor Injury2minor injury crashes9.5%
0.0%prior 2
Possible Injury3possible injury crashes14.3%
0.0%prior 3
No Injury14no injury crashes66.7%
0.0%prior 14

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'Followed too closely' doubled from 2 in March 2021 to 4 in March 2022. Conversely, 'Inattention' crashes slightly decreased from 5 to 4, while 'No improper driving' increased from 3 to 4 crashes. 'Driving too fast for conditions' emerged as a factor in March 2022 with 2 crashes, where it was not present in March 2021.

Officer-Reported Primary Contributing Cause

Inattention4 (19%)-20.0%prior 5
No improper driving4 (19%)
Followed too closely4 (19%)
Driving too fast for conditions2 (9.5%)
Failed to yield right of way2 (9.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4.8%)
Other improper action1 (4.8%)
Made an improper turn1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The number of crashes occurring on dry roads decreased from 18 in March 2021 to 14 in March 2022. In contrast, crashes on wet road surfaces saw a significant increase, rising from 1 in March 2021 to 6 in March 2022. Additionally, 1 crash in March 2022 was reported on an icy road surface, a condition not present in March 2021 crash data.

Weather

Clear14 (66.7%)
0.0%prior 14
Cloudy/Rain3 (14.3%)
Clear/Snow2 (9.5%)
Clear/Cloudy1 (4.8%)
Cloudy1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Weather condition at time of crash

Lighting

Daylight14 (66.7%)
7.7%prior 13
Dark - lighted roadway5 (23.8%)
-16.7%prior 6
Dusk2 (9.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Lighting condition field

Road Surface

Dry14 (66.7%)
-22.2%prior 18
Wet6 (28.6%)
Ice1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (36 vehicles)

1
HONDA9 (25%)
2
TOYOTA9 (25%)
28.6%prior 7
3
HYUNDAI3 (8.3%)
4
NISSAN2 (5.6%)
5
VOLVO2 (5.6%)
6
FORD2 (5.6%)
7
MAZDA1 (2.8%)
8
CHEVROLET1 (2.8%)
9
INFI1 (2.8%)
10
JEEP1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Vehicle unit records

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

Sex Distribution (39 persons with recorded sex)

Female23 (59.0%)
64.3%prior 14
Male16 (41.0%)
-23.8%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes at the 35 mph speed limit, which was the most common in both periods, slightly decreased from 11 in March 2021 to 10 in March 2022. Crashes at 30 mph increased from 1 to 2, and at 65 mph from 2 to 3. New speed zones appeared in March 2022 with 1 crash at 10 mph and 3 crashes at 55 mph, neither of which were present in March 2021 data.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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: 2022-03-01 through 2022-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-03-01 through 2022-03-31 (31 days)
  • Geographic scope: LONGMEADOW, MA
  • Total crash records analyzed: 21
  • Total persons involved: 42
  • Total vehicles involved: 36

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). "LONGMEADOW, MA Crash Intelligence Report: March 2022." Published June 21, 2026. Reporting period: 2022-03-01 to 2022-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/longmeadow/march-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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Longmeadow, MA Crash Report — March 2022 | ThatCarHitMe.com