Monthly Traffic Safety Analysis

30 CRASHES IN
AMHERST, MA
APRIL 2023

All metrics benchmarked againstApril 2022

Total crashes in April 2023 were 30, a 7.14% increase from the 28 crashes recorded in April 2022. A notable shift was the doubling of total injuries, from 3 in April 2022 to 6 in April 2023.

30

7.1%was 28

Total Crash Events

0

Persons Killed

6

100.0%was 3

Persons Injured

0

-100.0%was 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 · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Amherst, MA, showed a slight increase year-over-year, rising by 7.14% from 28 crashes in April 2022 to 30 crashes in April 2023. This indicates a modest upward trend in crash frequency for the specified period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

6

Motorists Injured

Prior: 3100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday in both periods, with 8 crashes in April 2022 and 9 in April 2023. However, the peak hour shifted from 5 PM with 5 crashes in April 2022 to 8 PM with 4 crashes in April 2023, suggesting a change in the most crash-prone time of day.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero for both April 2022 and April 2023. Total injuries doubled from 3 in the prior period to 6 in the current period. Minor injuries increased from 2 to 4, and possible injuries increased from 1 to 2, indicating a rise in less severe injury outcomes.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes13.3%
100.0%prior 2
Possible Injury2possible injury crashes6.7%
100.0%prior 1
No Injury24no injury crashes80%
0.0%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record

Top Contributing Factors

The contributing factor "Fatigued/asleep" increased significantly from 1 crash in April 2022 to 5 crashes in April 2023, a 400% increase in count. "Inattention" also rose from 4 crashes to 5 crashes, while "No improper driving" decreased from 4 crashes to 2 crashes.

Officer-Reported Primary Contributing Cause

Inattention5 (16.7%)
Fatigued/asleep5 (16.7%)
Disregarded traffic signs, signals, road markings3 (10%)
Failed to yield right of way3 (10%)
Failure to keep in proper lane or running off road3 (10%)
No improper driving2 (6.7%)
Other improper action2 (6.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.3%)
Distracted1 (3.3%)
Physical impairment1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in clear weather slightly increased from 21 to 23 year-over-year, remaining the most common condition. Crashes during "Daylight" decreased from 22 to 19, while those in "Dark - lighted roadway" doubled from 5 to 10. The number of crashes on wet road surfaces remained consistent at 5 for both periods.

Weather

Clear23 (76.7%)
9.5%prior 21
Rain2 (6.7%)
Rain/Cloudy2 (6.7%)
Clear/Cloudy1 (3.3%)
Clear/Unknown1 (3.3%)
Cloudy1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash

Lighting

Daylight19 (63.3%)
-13.6%prior 22
Dark - lighted roadway10 (33.3%)
100.0%prior 5
Dark - roadway not lighted1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field

Road Surface

Dry25 (83.3%)
8.7%prior 23
Wet5 (16.7%)
0.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 55 in April 2022 to 51 in April 2023. Toyota remained the most frequently involved make, though its count decreased from 15 to 11. The 16-20 age group saw a decrease in involved persons from 14 to 6, while the 45-54 age group increased from 4 to 10.

Top Vehicle Makes (51 vehicles)

1
TOYOTA11 (21.6%)
-26.7%prior 15
2
HONDA8 (15.7%)
33.3%prior 6
3
NISSAN6 (11.8%)
20.0%prior 5
4
SUBARU5 (9.8%)
5
FORD5 (9.8%)
0.0%prior 5
6
MAZDA3 (5.9%)
7
HYUNDAI3 (5.9%)
8
VOLVO2 (3.9%)
9
GILG2 (3.9%)
10
LEXUS1 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records

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

Sex Distribution (61 persons with recorded sex)

Male43 (70.5%)
26.5%prior 34
Female18 (29.5%)
-47.1%prior 34

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 35 mph speed zones decreased from 10 in April 2022 to 5 in April 2023. Conversely, crashes in 25 mph speed zones increased from 6 to 10 during the same period. There were no fatal crashes recorded in any speed zone for either year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-04-01 through 2023-04-30 (30 days)
  • Geographic scope: AMHERST, MA
  • Total crash records analyzed: 30
  • Total persons involved: 64
  • Total vehicles involved: 51

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). "AMHERST, MA Crash Intelligence Report: April 2023." Published June 21, 2026. Reporting period: 2023-04-01 to 2023-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/amherst/april-2023-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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Amherst, MA Crash Report — April 2023 | ThatCarHitMe.com