Monthly Traffic Safety Analysis

24 CRASHES IN
HANOVER, MA
MARCH 2022

All metrics benchmarked againstMarch 2021

Total crashes in Hanover, MA significantly increased by 166.67% from March 2021 to March 2022, rising from 9 crashes to 24 crashes. Concurrently, total injuries increased by 85.71%, from 7 to 13. The most notable shift was the substantial increase in overall crash volume and the emergence of DUI-related crashes in the current period.

24

166.7%was 9

Total Crash Events

0

Persons Killed

13

85.7%was 7

Persons Injured

0

Fatal Crash Events

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 activity in March 2022 saw a substantial increase compared to March 2021. Total crashes rose by 166.67%, from 9 crashes in the prior period to 24 crashes in the current period. Correspondingly, total injuries also increased by 85.71%, from 7 injuries in March 2021 to 13 injuries in March 2022. Fatalities remained at zero in both periods.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

12

Motorists Injured

Prior: 771.4%

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 remained Wednesday in both periods, increasing from 3 crashes in March 2021 to 8 crashes in March 2022. The peak hour shifted from 2 PM with 2 crashes in the prior period to 3 PM with 5 crashes in the current period. Crash distribution became broader across the week, with notable increases on Tuesday (from 0 to 4 crashes) and Saturday (from 1 to 6 crashes).

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

While total injuries increased from 7 to 13, the proportion of injury-involved crashes decreased from 55.5% in March 2021 to 33.3% in March 2022. Serious injuries (code A) increased from 0 in the prior period to 1 in the current period. Minor injuries (code B) remained stable at 2, while possible injuries (code C) increased from 3 to 5.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4.2%
Minor Injury2minor injury crashes8.3%
0.0%prior 2
Possible Injury5possible injury crashes20.8%
66.7%prior 3
No Injury15no injury crashes62.5%
275.0%prior 4

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

The top contributing factor, "Failed to yield right of way," increased from 3 crashes in March 2021 to 7 crashes in March 2022. "Followed too closely" also increased in count from 3 to 4 crashes, though its share decreased from 33.3% to 16.7%. "No improper driving" emerged as a significant factor in March 2022, contributing to 5 crashes (20.8% share), while it was not among the top factors in the prior period.

Officer-Reported Primary Contributing Cause

Failed to yield right of way7 (29.2%)
No improper driving5 (20.8%)
Followed too closely4 (16.7%)
Failure to keep in proper lane or running off road2 (8.3%)
Over-correcting/over-steering1 (4.2%)
Distracted1 (4.2%)
Physical impairment1 (4.2%)
Glare1 (4.2%)
Inattention1 (4.2%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4.2%)

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

Weather conditions were more varied in March 2022, with 12 crashes occurring in clear weather, 6 in cloudy, 3 in snow, 2 in rain, and 1 in cloudy/rain conditions. In contrast, March 2021 predominantly reported clear weather for all 9 crashes. There is no comparable data for lighting or road surface conditions for the prior period.

Weather

Clear12 (50.0%)
Cloudy6 (25.0%)
Snow3 (12.5%)
Rain2 (8.3%)
Cloudy/Rain1 (4.2%)

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

Lighting

Daylight15 (62.5%)
Dark - lighted roadway5 (20.8%)
Dusk3 (12.5%)
Dark - roadway not lighted1 (4.2%)

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

Road Surface

Dry18 (75.0%)
Wet6 (25.0%)

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 (45 vehicles)

1
TOYOTA9 (20%)
2
NISSAN6 (13.3%)
3
CHEVROLET5 (11.1%)
4
FORD4 (8.9%)
5
MERCEDES-BENZ3 (6.7%)
6
VOLVO2 (4.4%)
7
HONDA2 (4.4%)
8
INFI2 (4.4%)
9
SUBARU2 (4.4%)
10
VOLKSWAGEN2 (4.4%)

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

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

Sex Distribution (58 persons with recorded sex)

Male33 (56.9%)
200.0%prior 11
Female25 (43.1%)
150.0%prior 10

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 in the 35 mph speed zone saw a substantial increase, rising from 1 crash in March 2021 to 12 crashes in March 2022. The number of crashes in the 40 mph zone remained consistent at 6 in both periods. Additionally, March 2022 reported crashes in 20 mph (1), 30 mph (2), and 45 mph (2) zones, which were not present in the prior period's 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: HANOVER, MA
  • Total crash records analyzed: 24
  • Total persons involved: 62
  • Total vehicles involved: 45

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). "HANOVER, 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/hanover/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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Hanover, MA Crash Report — March 2022 | ThatCarHitMe.com